1279 Inference Jobs - Page 14

We, at Cogito, are looking for someone with a zeal and flair to curate knowledge pieces and writings on how Artificial Intelligence, Machine Learning & NLP have taken automation & efficiencies in various industries by storm and how these ever shape-shifting technologies are surprising humans themselves everyday. Cogito Technologies, having a strong presence in USA and its delivery centre in Delhi NCR, India, specializes in Human Empowered Automation. Our mission is to help our customers innovate and scale by solving their day-to-day data needs. Using our skilled on-demand workforce, we partner with Machine Learning, Artificial Intelligence, Technology and eCommerce clients to develop high-quality data sets used to build and enhance various cutting-edge business applications. Cogito is currently working on Artificial Intelligence applications in Annotation work and is looking to engage with "Content Manager" to participate in ongoing projects. The Role: Being Content manager you will be working closely with a team to read, write, summarize knowledge, and interpret meaning. Think of it like being a language arts teacher or a personal tutor for some of the world's most influential technology. Assist with development of Large Language Models Assist with development of Generative AI applications Evaluate and Grade responses of LLM models Content Summarization Model evaluation Model alignment Efficient inference Classification and categorization Sentiment analysis Multimodal model question-answering systems Skills Set: Fluent to native English writing and reading skills required University to Masters degree 8-15 years of extensive experience working as Content Writer Ability to answer free-form prompts (questions) across a general scope of topics Ability to reference online resources and rephrase and write cohesive, accurate, responsive, and sometimes empathetic answers to the prompts in the perspective of an AI model Proven track record working on other projects requiring free form sentence creation Ability to answer specialized domain free-form prompts at university-level difficulty Ability to provide cohesive explanations to their prompt responses (E.g., explaining the process of solving a given math question, listing out the detailed process for a software question, etc.) Extra Added advantage if you have: Up-to-date knowledge on US culture and news. Knowledge of various NLP tasks and algorithms, such as sentiment analysis, named entity recognition, text classification, machine translation, and language generation. The Person This is a technology job that accommodates humanities people and relies more fully on your competencies than your formal experience making it a rare opportunity that's perfect for new grads, career transitioners, and those seeking an exciting encore career in AI. You're the sort of person who is exceptional at generating copy intuitively. You've also got the metacognitive awareness to "show your work." In addition, you're the sort of person with a deep interest in linguistics. You instinctively document learning and continuously refine methods. You are a(n): Dedicated Grammarian Natural Writer Diligent Reader Self-Aware Interpreter Synthetic Sense-Maker Perpetual Learner Instinctive Educator Proven experience required Core Content Writing Background with own website/blogs/written piece of articles etc. Work in a cordial and cooperative manner with Marketing, SEO & Operations teams Most importantly, technical bent of mind with keen interest in new technologies and their applications The ability to think and act like a stakeholder is a plus Non-technical Strong sense of responsibility in quality and idea generation Can work well with others and open for giving/taking suggestions Strong written and verbal communication skills Strong motivation to learn and go in-depth into field of study Job requirements Fluent in English to be able to follow instructions and guidelines Detail-oriented with the ability to understand and follow instructions Ability to meet deadlines Responsible, reliable, and communicative Designation: Manager-Content Gender: Male/Female Work Location: Noida DOJ: ASAP Job Type: Full Time CTC: Best in the industry (will be discussed during call)Please apply here or email your updated resume: hr@anolytics.in --- Regards, Team HR Show more Show less

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Summary - We are seeking experts with a robust background in the field of deep learning (DL) to design state-of-the-art low-level perception (LLP) as well as end-to-end AD models, with a focus on achieving accuracy-latency Pareto optimality. This role involves comprehending state-of-the-art research in this field and deploying networks on the Qualcomm Ride platform for L2/L3 Advanced Driver Assistance Systems (ADAS) and autonomous driving. The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross-attention, Self-attention), lifting 2D features to Bird's Eye View (BEV) space, and their applications to multi-modal fusion. This position offers extensive opportunities to collaborate with advanced R&D teams of leading automotive Original Equipment Manufacturers (OEMs) as well as Qualcomm's internal stack teams. The team is responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks running on Snapdragon Ride AI accelerators. A thorough understanding of machine learning algorithms, particularly those related to automotive use cases (autonomous driving, vision, and LiDAR processing ML algorithms), is essential. Research experience in the development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization, and pruning is highly desirable. Strong communication and interpersonal skills are required, and the candidate must be able to work effectively with various horizontal AI teams. Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 1+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field. Preferred Qualifications: Good at software development with excellent analytical, development, and problem-solving skills. Strong understanding of Machine Learning fundamentals Hands-on experience with deep learning network design and implementation. Ability to define network from scratch in PyTorch, ability to add new loss function, modify network with torch.fx. Adept at version control system like GIT. Experience in neural network quantization, compression, pruning algorithms. Experience in deep learning kernel/compiler optimization Strong communication skills Principal Duties And Responsibilities: Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations. Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions. Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development. Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same. Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers. Conducts complex experiments to train and evaluate machine learning models and/or software independently. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail myhr.support@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3074561 Show more Show less

Hi All, We are hiring for a Generative AI Architect for one of our esteemed clients based in Gurgaon . Role Overview: We’re looking for an experienced Generative AI Architect to lead the design and implementation of scalable GenAI solutions for real-world applications. The ideal candidate will have a proven track record of deploying GenAI systems in production environments, handling performance optimization, data governance, model evaluation, and vector search enhancements. Key Responsibilities: Architect GenAI systems integrating LLMs, APIs, vector databases, and application layers Design scalable RAG pipelines and knowledge graph integrations Evaluate build vs. buy decisions; choose between open-source and commercial models Define reference architectures and reusable components for GenAI platforms Integrate MLOps/LLMOps for monitoring, versioning, and feedback mechanisms Technical Skills: Strong grasp of Transformer architectures , NLP pipelines, and fine-tuning techniques Hands-on with LangChain, LLamaIndex, Haystack Orchestration tools: Kubeflow, Airflow, Ray Experience with Vector DBs : Pinecone, FAISS, Weaviate, Milvus Cloud expertise in AWS, Azure, or GCP with hands-on GenAI tools Proficient in developing APIs/microservices for AI deployment Strong understanding of embeddings, tokenization, and inference tuning 📩 Interested candidates can send their profiles to: ruchi@intileo.com Please include the following details in your application: Current CTC Expected CTC Notice Period Current Location Brief note on your suitability for the role Looking forward to connecting with the right talent! #Hiring #GenerativeAI #AIArchitect #LLM #LangChain #VectorDB #AIJobs #Gurgaon #Intileo Show more Show less

As an AI Architect at Innovaccer, you will be at the forefront of designing, training, and fine-tuning foundational models with healthcare-specific data. You will be critical in integrating these technologies into our healthcare products, ensuring they operate effectively in a production environment. Your expertise will help us to revolutionize healthcare delivery, improve patient outcomes, and maintain compliance with industry regulations. A Day in Life Fine-tuning state-of-the-art small language models (SLMs) like Llama-3.1-8B or Phi-3.5-3B on diverse healthcare datasets. Evaluating and optimizing various inference and serving frameworks (e.g., Triton, TensorRT, VLLM, TGI). Read about the most recent AI model architectures. Collaborating with product teams to review and refine architecture designs incorporating AI. Troubleshooting AI deployment issues in customer environments, ensuring smooth operation and optimal performance. Authoring and presenting technical documentation and white papers and showcasing breakthroughs in internal and external forums. Responsibilities Design, train, and fine-tune advanced foundational models (text, audio, vision) using healthcare-specific datasets, focusing on accuracy and clinical relevance. Collaborate with cross-functional teams (product, engineering, clinical) to seamlessly integrate AI/ML technologies into our product offerings. Deploy, monitor, and manage AI models in a production environment, ensuring high availability, scalability, and performance. Continuously research and evaluate the latest advancements in AI/ML and healthcare industry trends to drive innovation within Innovaccer. Create high-quality intellectual property (white papers, case studies, conference presentations) showcasing Innovaccer's technical leadership. Ensure all AI solutions adhere to healthcare standards and regulatory requirements (HIPAA, GDPR, etc.). Develop and maintain comprehensive documentation for AI models, including development, training, fine-tuning, and deployment procedures. Provide technical guidance and mentorship to junior AI engineers and team members. Collaborate with stakeholders to understand clinical needs and translate them into technical requirements for model fine-tuning and development. Select and curate appropriate datasets for fine-tuning foundational models to address specific healthcare use cases. Qualifications Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Minimum of 7 years of hands-on experience in AI/ML, with a demonstrable track record of training and deploying LLMs and other machine learning models. Strong proficiency in Python and familiarity with popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers, etc.). Practical experience deploying and managing AI models in production environments, including expertise in serving and inference frameworks (Triton, TensorRT, VLLM, TGI, etc.). Proven experience in healthcare AI applications, including a solid understanding of healthcare data standards (FHIR, HL7) and regulatory compliance (HIPAA, SOC2, NIST). Excellent problem-solving and analytical abilities, capable of tackling complex challenges and evaluating multiple factors. Exceptional communication and collaboration skills, enabling effective teamwork in a dynamic environment. A strong publication record in top-tier AI/ML conferences (NeurIPS, ICML, KDD, CVPR, AAMAS, etc.) is highly desirable. Experience with cloud computing platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) is a plus. Show more Show less

Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It With Pride. You will be crucial in supporting our business by creating valuable, actionable insights about the data, and communicating your findings to the business. You will work with various stakeholders to determine how to use business data for business solutions/insights. How You Will Contribute You will: Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization. In this role you will also formulate hypotheses and test them using math, statistics, visualization and predictive modeling Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business. After that you will work with stakeholders to determine how to use business data for business solutions/insights Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications. Coordinate with other technical/functional teams to implement models and monitor results Apply mathematical, statistical, predictive modelling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy Evaluate the need for analytics, assess the problems to be solved and what internal or external data sources to use or acquire. Specify and apply appropriate mathematical, statistical, predictive modelling or machine-learning techniques to analyze data, generate insights, create value and support decision making Contribute to exploration and experimentation in data visualization and you will manage reviews of the benefits and value of analytics techniques and tools and recommend improvements What You Will Bring A desire to drive your future and accelerate your career and the following experience and knowledge: Strong quantitative skillset with experience in statistics and linear algebra. A natural inclination toward solving complex problems Knowledge/experience with statistical programming languages including R, Python, SQL, etc., to process data and gain insights from it Knowledge of machine learning techniques including decision-tree learning, clustering, artificial neural networks, etc., and their pros and cons Knowledge and experience in advanced statistical techniques and concepts including, regression, distribution properties, statistical testing, etc. Good communication skills to promote cross-team collaboration Multilingual coding knowledge/experience: Java, JavaScript, C, C++, etc. Experience/knowledge in statistics and data mining techniques including random forest, GLM/regression, social network analysis, text mining, etc. Ability to use data visualization tools to showcase data for stakeholders About The Role We are seeking a highly motivated and experienced Senior Data Scientist to join our team and spearhead the development of Generative AI (GenAI) capabilities within Mondelēz International from an enterprise application perspective. In this pivotal role, you will champion the full lifecycle of GenAI application projects, taking ownership from initial concept and design to successful deployment, ongoing optimization, and continuous improvement. Beyond project execution, you will serve as a strategic advisor, guiding the evolution of our GenAI capabilities and ensuring alignment with overarching business objectives. This includes defining and enforcing internal standards for GenAI application development, guaranteeing compliance with ethical and security guidelines. You will also support the design of enterprise-level logical architectures for typical GenAI applications, and evaluate and recommend the most appropriate tools and technologies to empower our GenAI initiatives. Ultimately, you will play a critical role in shaping the future of GenAI within Mondelēz, driving innovation, maximizing value realization, and fostering responsible AI adoption across the enterprise. Key Responsibilities: GenAI Application development: Serve as the tech lead from data science point of view in the complete lifecycle of GenAI application projects, from initial ideation and design to successful deployment, optimization, and continuous improvement. Include both in house development or partner collaboration. Strategic Advisory: Provide strategic advice on the evolution of our GenAI capabilities to match company goals. Keeping up with the latest GenAI trend and map that to Mondelez application context to enable us do things better and smarter. Standards and Governance: Help establish and enforce programmatic approaches, governance frameworks and best practices for effective GenAI application building. Responsible AI for GenAI applications, data protection in GenAI context, complying to regulatory requirements and cost-effective GenAI application deployment. Enterprise Architecture Support: Support the design and development of enterprise-level logical architectures for typical GenAI applications, ensuring scalability, maintainability, and integration with existing infrastructure. Technology Evaluation and Recommendation: Evaluate and recommend the most appropriate GenAI tools, technologies, and platforms to empower our GenAI initiatives, staying abreast of the latest advancements in the field with a focus on cloud-based tools/technologies. Knowledge Sharing and Mentoring: Share knowledge and expertise with other team members, mentor junior data scientists, and spearhead the development of a strong GenAI community within Mondelēz. Skills and Experiences: Deep understanding of data science methodologies and implications: proficiency in machine learning, deep learning, statistical modelling, optimization, causal inference etc. Experience in mapping business problems to such methodologies with clear understanding/consideration in Ethical implications, risk mitigation, integration requirements, resource demand/optimization etc. Hands-on experience in cloud environment (8 years): Cloud platform, cloud-based data storage, processing, AI/ML model building, model life cycle, process orchestration, cost optimization etc. Working experience with MLOps (5 years): Understand MLOps processes and practice, familiar with MLOps Tools and technologies. Contributed significantly to shaping MLOps practice in an enterprise setup. LLM Application architecture & Integration (3 years): Hands-on experience building RAG applications, clear understanding of the underline technologies. Extensive experience integrating LLM into workflow through different ways (API etc). Experience in build Agent to leverage LLM and other tools for complex tasks. Familiar with Agent frameworks and orchestration tools. Core GenAI expertise (3 years): Prompt Engineering, Agentic Framework, Model fine-tuning. Cloud Based Deployment & Scaling (LLM-Specific): Practical experience deploying and scaling LLM-based applications in cloud environment. Familiar with scaling strategies for LLMs, and integration with other application. Collaboration with cross-functional teams (5 years): Proven ability to collaborate effectively with cross-functional teams. Excellent communication skills, both written and verbal to articulate technical concepts. Qualifications: Master’s degree in a Quantitative Discipline, PhD preferred. Minimum 12+ years of experience in data science/AI. Minimum 3 years of GenAI focused experience. Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy Business Unit Summary At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about. We have a rich portfolio of strong brands globally and locally including many household names such as Oreo , belVita and LU biscuits; Cadbury Dairy Milk , Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum. Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen—and happen fast. Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Job Type Regular Data Science Analytics & Data Science Show more Show less

Position Overview Job Title: AI Engineer Location: Pune, India Role Description Indra is the central program driving the introduction and safe scaling of AI at DB. Focus is identify AI potential across various banking operations, driving funded use cases into production to create value and confidence and scale across the bank, creating selected shared services with embedded safety to enable low cost scale, developing an AI Workbench for developers for safe AI development at pace, and introducing AI controls whilst aiming to maintain time to market. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your Key Responsibilities Model Deployment: Collaborate with data scientists to deploy machine learning models into production environments. Implement deployment strategies such as A/B testing or canary releases to ensure safe and controlled rollouts. Infrastructure Management: Design and manage the infrastructure required for hosting ML models, including cloud resources and on-premises servers. Utilize containerization technologies like Docker to package models and dependencies. Continuous Integration/Continuous Deployment (CI/CD): Develop and maintain CI/CD pipelines for automating the testing, integration, and deployment of ML models. Implement version control to track changes in both code and model artifacts. Monitoring and Logging: Establish monitoring solutions to track the performance and health of deployed models. Set up logging mechanisms to capture relevant information for debugging and auditing purposes. Scalability and Resource Optimization: Optimize ML infrastructure for scalability and cost-effectiveness. Implement auto-scaling mechanisms to handle varying workloads efficiently. Security and Compliance: Enforce security best practices to safeguard both the models and the data they process. Ensure compliance with industry regulations and data protection standards. Data Management: Oversee the management of data pipelines and data storage systems required for model training and inference. Implement data versioning and lineage tracking to maintain data integrity. Collaboration with Cross-Functional Teams: Work closely with data scientists, software engineers, and other stakeholders to understand model requirements and system constraints. Collaborate with DevOps teams to align MLOps practices with broader organizational goals. Performance Optimization: Continuously optimize and fine-tune ML models for better performance. Identify and address bottlenecks in the system to enhance overall efficiency. Documentation: Maintain clear and comprehensive documentation of MLOps processes, infrastructure, and model deployment procedures. Document best practices and troubleshooting guides for the team. Your Skills And Experience University degree in a technical or quantitative field (e.g., computer science, mathematics, physics, economics, etc.), preferably a Master’s or Doctoral degree 2-4 years of experience in applying AI, machine learning and/or data science in business and/or academia. Strong knowledge of at least one programming language (e.g., Python, JavaScript) and relevant data science or engineering framework (e.g., scikit-learn, TensorFlow, Spark, etc.). Ideally, practical experience in finance and banking Comfortable working with and managing uncertainty and ambiguity Excellent oral and written communication skills in English How We’ll Support You Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment. Show more Show less

Job Title: VP-Digital Expert Support Lead Experience : 15 + Years Location : Pune Position Overview The Digital Expert Support Lead is a senior-level leadership role responsible for ensuring the resilience, scalability, and enterprise-grade supportability of AI-powered expert systems deployed across key domains like Wholesale Banking, Customer Onboarding, Payments, and Cash Management . This role requires technical depth, process rigor, stakeholder fluency , and the ability to lead cross-functional squads that ensure seamless operational performance of GenAI and digital expert agents in production environments. The candidate will work closely with Engineering, Product, AI/ML, SRE, DevOps, and Compliance teams to drive operational excellence and shape the next generation of support standards for AI-driven enterprise systems. Role-Level Expectations Functionally accountable for all post-deployment support and performance assurance of digital expert systems. Operates at L3+ support level , enabling L1/L2 teams through proactive observability, automation, and runbook design. Leads stability engineering squads , AI support specialists, and DevOps collaborators across multiple business units. Acts as the bridge between operations and engineering , ensuring technical fixes feed into product backlog effectively. Supports continuous improvement through incident intelligence, root cause reporting, and architecture hardening . Sets the support governance framework (SLAs/OLAs, monitoring KPIs, downtime classification, recovery playbooks). Position Responsibilities Operational Leadership & Stability Engineering Own the production health and lifecycle support of all digital expert systems across onboarding, payments, and cash management. Build and govern the AI Support Control Center to track usage patterns, failure alerts, and escalation workflows. Define and enforce SLAs/OLAs for LLMs, GenAI endpoints, NLP components, and associated microservices. Establish and maintain observability stacks (Grafana, ELK, Prometheus, Datadog) integrated with model behavior. Lead major incident response and drive cross-functional war rooms for critical recovery. Ensure AI pipeline resilience through fallback logic, circuit breakers, and context caching. Review and fine-tune inference flows, timeout parameters, latency thresholds, and token usage limits. Engineering Collaboration & Enhancements Drive code-level hotfixes or patches in coordination with Dev, QA, and Cloud Ops. Implement automation scripts for diagnosis, log capture, reprocessing, and health validation. Maintain well-structured GitOps pipelines for support-related patches, rollback plans, and enhancement sprints. Coordinate enhancement requests based on operational analytics and feedback loops. Champion enterprise integration and alignment with Core Banking, ERP, H2H, and transaction processing systems. Governance, Planning & People Leadership Build and mentor a high-caliber AI Support Squad – support engineers, SREs, and automation leads. Define and publish support KPIs , operational dashboards, and quarterly stability scorecards. Present production health reports to business, engineering, and executive leadership. Define runbooks, response playbooks, knowledge base entries, and onboarding plans for newer AI support use cases. Manage relationships with AI platform vendors, cloud ops partners, and application owners. Must-Have Skills & Experience 15+ years of software engineering, platform reliability, or AI systems management experience. Proven track record of leading support and platform operations for AI/ML/GenAI-powered systems . Strong experience with cloud-native platforms (Azure/AWS), Kubernetes , and containerized observability . Deep expertise in Python and/or Java for production debugging and script/tooling development. Proficient in monitoring, logging, tracing, and alerts using enterprise tools (Grafana, ELK, Datadog). Familiarity with token economics , prompt tuning, inference throttling, and GenAI usage policies. Experience working with distributed systems, banking APIs, and integration with Core/ERP systems . Strong understanding of incident management frameworks (ITIL) and ability to drive postmortem discipline . Excellent stakeholder management, cross-functional coordination, and communication skills. Demonstrated ability to mentor senior ICs and influence product and platform priorities. Nice-to-Haves Exposure to enterprise AI platforms like OpenAI, Azure OpenAI, Anthropic, or Cohere. Experience supporting multi-tenant AI applications with business-driven SLAs. Hands-on experience integrating with compliance and risk monitoring platforms. Familiarity with automated root cause inference or anomaly detection tooling. Past participation in enterprise architecture councils or platform reliability forums Show more Show less

Role name: Automation Test Lead Years of exp : 5 - 8 yrs About Dailoqa Dailoqa’s mission is to bridge human expertise and artificial intelligence to solve the challenges facing financial services. Our founding team of 20+ international leaders, including former CIOs and senior industry experts, combines extensive technical expertise with decades of real-world experience to create tailored solutions that harness the power of combined intelligence. With a focus on Financial Services clients, we have deep expertise across Risk & Regulations, Retail & Institutional Banking, Capital Markets, and Wealth & Asset Management. Dailoqa has global reach in UK, Europe, Africa, India, ASEAN, and Australia. We integrate AI into business strategies to deliver tangible outcomes and set new standards for the financial services industry. Working at Dailoqa will be hard work, our environment is fluid and fast-moving and you'll be part of a community that values innovation, collaboration, and relentless curiosity. We’re looking at people who: Are proactive, curious adaptable, and patient Shape the company's vision and will have a direct impact on its success. Have the opportunity for fast career growth. Have the opportunity to participate in the upside of an ultra-growth venture. Have fun 🙂 Don’t apply if: You want to work on a single layer of the application. You prefer to work on well-defined problems. You need clear, pre-defined processes. You prefer a relaxed and slow paced environment. Role Overview As an Automation Test Lead at Dailoqa, you’ll architect and implement robust testing frameworks for both software and AI/ML systems. You’ll bridge the gap between traditional QA and AI-specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance. Key Responsibilities Test Automation Strategy & Framework Design Design and implement scalable test automation frameworks for frontend (UI/UX), backend APIs, and AI/ML model-serving endpoints using tools like Selenium, Playwright, Postman, or custom Python/Java solutions. Build GenAI-specific test suites for validating prompt outputs, LLM-based chat interfaces, RAG systems, and vector search accuracy. Develop performance testing strategies for AI pipelines (e.g., model inference latency, resource utilization). Continuous Testing & CI/CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions, Jenkins, or GitLab CI/CD. Implement shift-left testing by embedding automated checks into development workflows (e.g., unit tests, contract testing). AI/ML Model Validation Collaborate with data scientists to test AI/ML models for accuracy, fairness, stability, and bias mitigation using tools like TensorFlow Model Analysis or MLflow. Validate model drift and retraining pipelines to ensure consistent performance in production. Quality Metrics & Reporting Define and track KPIs: Test coverage (code, data, scenarios) Defect leakage rate Automation ROI (time saved vs. maintenance effort) Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews. Drive adoption of AI-specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation). Technical Requirements Must-Have 5–8 years in test automation, with 2+ years validating AI/ML systems. Expertise in: Automation tools: Selenium, Playwright, Cypress, REST Assured, Locust/JMeter CI/CD: Jenkins, GitHub Actions, GitLab AI/ML testing: Model validation, drift detection, GenAI output evaluation Languages: Python, Java, or JavaScript Certifications: ISTQB Advanced, CAST, or equivalent. Experience with MLOps tools: MLflow, Kubeflow, TFX Familiarity with vector databases (Pinecone, Milvus) and RAG workflows. Strong programming/scripting experience in JavaScript, Python, Java, or similar Experience with API testing, UI testing, and automated pipelines Understanding of AI/ML model testing, output evaluation, and non-deterministic behavior validation Experience with testing AI chatbots, LLM responses, prompt engineering outcomes, or AI fairness/bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile/Scrum methodology and tools like Azure Boards Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development. Ability to communicate technical risks to non-technical stakeholders. Collaborative mindset to work with cross-functional teams (data scientists, ML engineers, DevOps). Show more Show less

About Rapido We are India’s largest bike-taxi platform, steadily venturing into Auto, Delivery, Rental, and more. Currently, present in ~100 cities, we are growing close to ~50% year-on-year with steady funding. We have changed the concept of intra-city travel and made last-mile connectivity affordable to all. Along with being the #1 choice of 40 million people, we have also built a solid captain base of over 5 million registered captains, who have bettered their lives with Rapido. As an employer, we provide a lot of ownership to our team members providing multiple avenues for them to grow within the company. You will only grow with us with the right balance of ambition, fun, and transparent work culture! Job Summary: As a Senior Data Scientist your will be responsible for understanding product/business priorities, conducting opportunity analysis, defining product level metrics, setting metric targets, building data-driven hypothesis, and running high-quality experiments to hit those targets.A Senior Data Scientist should have an experienced of solving complex data analysis and machine learning problems in a real-world product setting. The role requires someone who is very comfortable working across teams, good at communicating and able to drive analysis and manage multiple streams. Your role would also require you to mentor junior Data Scientists in their learning and development. You will be part of a dynamic team and regularly work with colleagues from other verticals to co-ordinate and collaborate within an increasingly interconnected Data Science team here @ Rapido. Job Responsibilities: ● Translating business requirements into analytical solutions ● Do hands-on data analysis, using statistical techniques ● Pre-processing of structured and unstructured data ● Should be able to steer direction related to improving data collection for analytical systems ● Should be proficient in model development, validation and then roll-out ● Understand business challenges and goals to formulate the approach for data analysis and model creation ● Tune the model(s) to improve results provided over time ● Create an analytics roadmap for the project ● Collaborate with a technology/data engineering team to transfer the business understanding, get the model productionized and validate the output ● Work in highly collaborative teams that strive to build quality systems and provide business value ● Articulate insights and story telling for the senior management ● Mentor Junior Data team members in their learning and development Job Requirements: ● Work experience - 4 years as a Data Scientist or equivalent position and overall 6 years ● Masters or Ph.D. in Statistics, Math, CS, Econ, Physics, Engineering or related scientific disciplines; ● Passion for understanding business problems and trying to address them by leveraging data - characterized by high-volume, high dimensionality from multiple sources ● Experience with building predictive statistical, behavioral or other models via supervised and unsupervised machine learning, statistical analysis, and other predictive modeling techniques. ● Worked in a big data environment before alongside a data engineering team (and data visualization team, data and business analysts) ● Statistical knowledge - Proven experience in statistical methods like and not limited to Markov Models, Stochastic models, Bayesian Models, Classification Models, Cluster Analysis, Multivariate Stats, Regression Models, Ensemble Techniques ● Machine Learning - Prior work experience in one or more of these knowledge areas (domain agnostic): Price Modeling, Demand Forecasting, Recommender Systems, User Profiling, Fraud Detectors ● Experience in SQL is must ● Technologies - Proficiency in Python (must have) and any other prog. language; Specific libraries may include - Scikit-learn, pandas, TensorFlow, Keras, Torch, Caffe, Theano, etc; ● Experience of Pyspark is a plus ● Experience with A/B Testing framework ● Experience in managing a small team of data scientists is a plus What’s there for you? ● If you are excited to solve Complex Business problems at scale where you will cater to 10 million rides in a day across 100 cities, no better place to be. ● You can go swimming in our 100s of TBs of data on self-managed databases ● Opportunity to contribute in solving challenging problems like supply-demand matching, demand forecasting, ROI optimization, Segmentation, Causal Inference and many more. ● We have a very flat hierarchy and collaboration is our success mantra ● Chance to work with a lean team of highly talented and motivated people across all levels ● You will be working with cross functional teams and have a great learning curve and business exposure. Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Job Location: Hyderabad More Details Below About the team: Join the growing team at Qualcomm focused on advancing state-of-the-art in Machine Learning. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of trained neural networks on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. See your work directly impact billions of devices around the world. Responsibilities In this position, you will be responsible for the development and commercialization of ML solutions like Snapdragon Neural Processing Engine (SNPE) SDK on Qualcomm SoCs. You will be developing various SW features in our ML stack. You would be porting AI/ML solutions to various platforms and optimize the performance on multiple hardware accelerators (like CPU/GPU/NPU). You will have expert knowledge in deployment aspects of large software C/C++ dependency stacks using best practices. You will also have to keep up with the fast-paced development happening in the industry and academia to continuously enhance our solution from software engineering as well as machine learning standpoint. Work Experience 7-9 years of relevant work experience in software development. Live and breathe quality software development with excellent analytical and debugging skills. Strong understanding about Processor architecture, system design fundamentals. Experience with embedded systems development or equivalent. Strong development skills in C and C++. Excellent communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Experience in embedded system development. Experience in C, C++, OOPS and Design patterns. Experience in Linux kernel or driver development is a plus. Strong OS concepts. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3072303 Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary Job Description Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements Master’s/Bachelor’s degree in computer science or equivalent. 2-4 years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong in C/C++ programming, Design Patterns and OS concepts. Good scripting skills in Python. Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3075196 Show more Show less

Our Company Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI, and autonomous intelligent systems. We design intelligent platforms that solve complex business problems and deliver measurable impact through cutting-edge AI Overview : We are seeking an experienced Solution Architect with a strong foundation in software architecture and a working knowledge of AI-based products or platforms. In this role, you will be responsible for designing robust, scalable, and secure architectures that support AI-driven applications and enterprise systems. You will work closely with cross-functional teamsincluding data scientists, product managers, and engineering leadsto bridge the gap between business needs, technical feasibility, and AI we are looking from an ideal candidate ? Architect end-to-end solutions for enterprise and product-driven platforms, including components such as data pipelines, APIs, AI model integration, cloud infrastructure, and user interfaces. Guide teams in selecting the right technologies, tools, and design patterns to build scalable systems. Collaborate with AI/ML teams to understand model requirements and ensure smooth deployment and integration into production. Define system architecture diagrams, data flow, service orchestration, and infrastructure provisioning using modern tools. Work closely with stakeholders to translate business needs into technical solutions, with a focus on scalability, performance, and security. Provide leadership on best practices for software development, DevOps, and cloud-native architecture. Conduct architecture reviews and ensure alignment with security, compliance, and performance Skills : What skills do you need ? Requirements 10+ years of experience in software architecture or solution design roles. Proven experience designing systems using microservices, RESTful APIs, event-driven architecture, and cloud-native technologies. Hands-on experience with at least one major cloud provider: AWS, GCP, or Azure. Familiarity with AI/ML platforms or components, such as integrating AI models, MLOps pipelines, or inference services. Understanding of data architectures, including data lakes, streaming, and ETL pipelines. Strong experience with containerization (Docker, Kubernetes) and DevOps principles. Ability to lead technical discussions, make design trade-offs, and communicate with both technical and non-technical Qualifications : Exposure to AI model lifecycle management, prompt engineering, or real-time inference workflows. Experience with infrastructure-as-code (Terraform, Pulumi). Knowledge of GraphQL, gRPC, or serverless architectures. Previous experience working in AI-driven product companies or digital transformation We Offer : High-impact role in designing intelligent systems that shape the future of AI adoption. Work with forward-thinking engineers, researchers, and innovators. Strong focus on career growth, learning, and technical leadership. Compensation is not a constraint for the right candidate. (ref:hirist.tech) Show more Show less

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI, and autonomous intelligent systems. We build intelligent, cutting-edge solutions designed to scale and evolve with the future of artificial intelligence. Role Overview We are looking for a skilled and versatile AI Infrastructure Engineer (DevOps/MLOps) to build and manage the cloud infrastructure, deployment pipelines, and machine learning operations behind our AI-powered products. You will work at the intersection of software engineering, ML, and cloud architecture to ensure that our models and systems are scalable, reliable, and production-ready. Key Responsibilities Design and manage CI/CD pipelines for both software applications and machine learning workflows. Deploy and monitor ML models in production using tools like MLflow, SageMaker, Vertex AI, or similar. Automate the provisioning and configuration of infrastructure using IaC tools (Terraform, Pulumi, etc. Build robust monitoring, logging, and alerting systems for AI applications. Manage containerized services with Docker and orchestration platforms like Kubernetes. Collaborate with data scientists and ML engineers to streamline model experimentation, versioning, and deployment. Optimize compute resources and storage costs across cloud environments (AWS, GCP, or Azure). Ensure system reliability, scalability, and security across all environments. Requirements 5+ years of experience in DevOps, MLOps, or infrastructure engineering roles. Hands-on experience with cloud platforms (AWS, GCP, or Azure) and services related to ML workloads. Strong knowledge of CI/CD tools (e.g, GitHub Actions, Jenkins, GitLab CI). Proficiency in Docker, Kubernetes, and infrastructure-as-code frameworks. Experience with ML pipelines, model versioning, and ML monitoring tools. Scripting skills in Python, Bash, or similar for automation tasks. Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, CloudWatch, etc. Understanding of ML lifecycle management and reproducibility. Preferred Qualifications Experience with Kubeflow, MLflow, DVC, or Triton Inference Server. Exposure to data versioning, feature stores, and model registries. Certification in AWS/GCP DevOps or Machine Learning Engineering is a plus. Background in software engineering, data engineering, or ML research is a bonus. What We Offer Work on cutting-edge AI platforms and infrastructure. Cross-functional collaboration with top ML, research, and product teams. Competitive compensation package - no constraints for the right candidate. (ref:hirist.tech) Show more Show less

Job Title : Senior Data Scientist Algorithmic Trading & Capital Markets Job Locations : Noida | Pune | Mumbai (Currently Work From Home) About The Role We are seeking an experienced and highly motivated Senior Data Scientist to join our dynamic team focused on Algorithmic Trading and Capital Markets. The ideal candidate will bring a strong academic background and a minimum of 7 years of relevant industry experience in data science and financial domains. Key Responsibilities Develop and optimize quantitative models for algorithmic trading strategies. Apply statistical inference, machine learning, and financial mathematics to capital market problems. Conduct research and analysis on derivatives pricing, risk modeling, and portfolio optimization. Work closely with cross-functional teams including traders, quants, and software engineers. Handle large datasets using Python, Pandas, and Numpy for deep analysis and model development. Design and manage databases for efficient data retrieval and storage. Required Qualifications Masters or Ph.D. in a Quantitative Field such as Computer Science, Mathematics, Statistics, Financial Engineering, or related disciplines. 7+ years of relevant experience in Data Science, preferably in capital markets or finance in : Python, Pandas, Numpy Statistical inference & machine learning techniques Financial mathematics & derivatives pricing Optimization theory Database technologies Job Perks Opportunity to work on cutting-edge financial and trading models. Collaborative and research-driven work environment. Flexible WFH setup (until further notice) (ref:hirist.tech) Show more Show less

Omni's team is passionate about Commerce and Digital Transformation. We've been successfully delivering Commerce solutions for clients across North America, Europe, Asia, and Australia. The team has experience executing and delivering projects in B2B and B2C solutions. Job Description This is a remote position. We are seeking a Senior Data Engineer to architect and build robust, scalable, and efficient data systems that power AI and Analytics solutions. You will design end-to-end data pipelines, optimize data storage, and ensure seamless data availability for machine learning and business analytics use cases. This role demands deep engineering excellence balancing performance, reliability, security, and cost to support real-world AI applications. Key Responsibilities Architect, design, and implement high-throughput ETL/ELT pipelines for batch and real-time data processing. Build cloud-native data platforms : data lakes, data warehouses, feature stores. Work with structured, semi-structured, and unstructured data at petabyte scale. Optimize data pipelines for latency, throughput, cost-efficiency, and fault tolerance. Implement data governance, lineage, quality checks, and metadata management. Collaborate closely with Data Scientists and ML Engineers to prepare data pipelines for model training and inference. Implement streaming data architectures using Kafka, Spark Streaming, or AWS Kinesis. Automate infrastructure deployment using Terraform, CloudFormation, or Kubernetes operators. Requirements 7+ years in Data Engineering, Big Data, or Cloud Data Platform roles. Strong proficiency in Python and SQL. Deep expertise in distributed data systems (Spark, Hive, Presto, Dask). Cloud-native engineering experience (AWS, GCP, Azure) : BigQuery, Redshift, EMR, Databricks, etc. Experience designing event-driven architectures and streaming systems (Kafka, Pub/Sub, Flink). Strong background in data modeling (star schema, OLAP cubes, graph databases). Proven experience with data security, encryption, compliance standards (e.g., GDPR, HIPAA). Preferred Skills Experience in MLOps enablement : creating feature stores, versioned datasets. Familiarity with real-time analytics platforms (Clickhouse, Apache Pinot). Exposure to data observability tools like Monte Carlo, Databand, or similar. Passionate about building high-scale, resilient, and secure data systems. Excited to support AI/ML innovation with state-of-the-art data infrastructure. Obsessed with automation, scalability, and best engineering practices. (ref:hirist.tech) Show more Show less

Job Description We are seeking a high-impact AI/ML Engineer to lead the design, development, and deployment of machine learning and AI solutions across vision, audio, and language modalities. You'll be part of a fast-paced, outcome-oriented AI & Analytics team, working alongside data scientists, engineers, and product leaders to transform business use cases into real-time, scalable AI systems. This role demands strong technical leadership, a product mindset, and hands-on expertise in Computer Vision, Audio Intelligence, and Deep Learning. Key Responsibilities Architect, develop, and deploy ML models for multimodal problems, including vision (image/video), audio (speech/sound), and NLP tasks. Own the complete ML lifecycle : data ingestion, model development, experimentation, evaluation, deployment, and monitoring. Leverage transfer learning, foundation models, or self-supervised approaches where suitable. Design and implement scalable training pipelines and inference APIs using frameworks like PyTorch or TensorFlow. Collaborate with MLOps, data engineering, and DevOps to productionize models using Docker, Kubernetes, or serverless infrastructure. Continuously monitor model performance and implement retraining workflows to ensure accuracy over time. Stay ahead of the curve on cutting-edge AI research (e.g., generative AI, video understanding, audio embeddings) and incorporate innovations into production systems. Write clean, well-documented, and reusable code to support agile experimentation and long-term platform : Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 58+ years of experience in AI/ML Engineering, with at least 3 years in applied deep learning. Technical Skills Languages : Expert in Python; good knowledge of R or Java is a plus. ML/DL Frameworks : Proficient with PyTorch, TensorFlow, Scikit-learn, ONNX. Computer Vision : Image classification, object detection, OCR, segmentation, tracking (YOLO, Detectron2, OpenCV, MediaPipe). Audio AI : Speech recognition (ASR), sound classification, audio embedding models (Wav2Vec2, Whisper, etc.). Data Engineering : Strong with Pandas, NumPy, SQL, and preprocessing pipelines for structured and unstructured data. NLP/LLMs : Working knowledge of Transformers, BERT/LLAMA, Hugging Face ecosystem is preferred. Cloud & MLOps : Experience with AWS/GCP/Azure, MLFlow, SageMaker, Vertex AI, or Azure ML. Deployment & Infrastructure : Experience with Docker, Kubernetes, REST APIs, serverless ML inference. CI/CD & Version Control : Git, DVC, ML pipelines, Jenkins, Airflow, etc. Soft Skills & Competencies Strong analytical and systems thinking; able to break down business problems into ML components. Excellent communication skills able to explain models, results, and decisions to non-technical stakeholders. Proven ability to work cross-functionally with designers, engineers, product managers, and analysts. Demonstrated bias for action, rapid experimentation, and iterative delivery of impact. (ref:hirist.tech) Show more Show less

Company Description At Blend, we are award-winning experts who transform businesses by delivering valuable insights that make a difference. From crafting a data strategy that focuses resources on what will make the biggest difference to your company, to standing up infrastructure, and turning raw data into value through data science and visualization: we do it all. We believe that data that doesn't drive value is lost opportunity, and we are passionate about helping our clients drive better outcome through applied analytics. We are obsessed with delivering world class solutions to our customers through our network of industry leading partners. If this sounds like your kind of challenge, we would love to hear from you. For more information, visit www.blend360.com Job Description We are looking for someone who is ready for the next step in their career and is excited by the idea of solving problems and designing best in class. However, they also need to be aware of the practicalities of making a difference in the real world – whilst we love innovative advanced solutions, we also believe that sometimes a simple solution can have the most impact. Our AI Engineer is someone who feels the most comfortable around solving problems, answering questions and proposing solutions. We place a high value on the ability to communicate and translate complex analytical thinking into non-technical and commercially oriented concepts, and experience working on difficult projects and/or with demanding stakeholders is always appreciated. What can you expect from the role? Contribute to design, develop, deploy and maintain AI solutions Use a variety of AI Engineering tools and methods to deliver Own parts of projects end-to-end Contributing to solutions design and proposal submissions Supporting the development of the AI engineering team within Blend Maintain in-depth knowledge of the AI ecosystems and trends Mentor junior colleagues Qualifications Contribute to the design, development, testing, deployment, maintenance, and improvement of robust, scalable, and reliable software systems, adhering to best practices. Apply Python programming skills for both software development and AI/ML tasks. Utilize analytical and problem-solving skills to debug complex software, infrastructure, and AI integration issues. Proficiently use version control systems, especially Git and ML/LLMOps model versioning protocols. Assist in analysing complex or ambiguous AI problems, breaking them down into manageable tasks, and contributing to conceptual solution design within the rapidly evolving field of generative AI. Work effectively within a standard software development lifecycle (e.g., Agile, Scrum). Contribute to the design and utilization of scalable systems using cloud services (AWS, Azure, GCP), including compute, storage, and ML/AI services. (Preferred: Azure) Participate in designing and building scalable and reliable infrastructure to support AI inference workloads, including implementing APIs, microservices, and orchestration layers. Contribute to the design, building, or working with event-driven architectures and relevant technologies (e.g., Kafka, RabbitMQ, cloud event services) for asynchronous processing and system integration. Experience with containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes, Airflow, Kubeflow, Databricks Jobs, etc). Assist in implementing CI/CD pipelines and optionally using IaC principles/tools for deploying and managing infrastructure and ML/LLM models. Contribute to developing and deploying LLM-powered features into production systems, translating experimental outputs into robust services with clear APIs. Demonstrate familiarity with transformer model architectures and a practical understanding of LLM specifics like context handling. Assist in designing, implementing, and optimising prompt strategies (e.g., chaining, templates, dynamic inputs); practical understanding of output post-processing. Experience integrating with third-party LLM providers, managing API usage, rate limits, token efficiency, and applying best practices for versioning, retries, and failover. Contribute to coordinating multi-step AI workflows, potentially involving multiple models or services, and optimising for latency and cost (sequential vs. parallel execution). Assist in monitoring, evaluating, and optimising AI/LLM solutions for performance (latency, throughput, reliability), accuracy, and cost in production environments. Additional Information Experience specifically with the Databricks MLOps platform. Familiarity with fine-tuning classical LLM models. Experience ensuring security and observability for AI services. Contribution to relevant open-source projects. Familiarity with building agentic GenAI modules or systems. Have hands-on experience implementing and automating MLOps/LLMOps practices, including model tracking, versioning, deployment, monitoring (latency, cost, throughput, reliability), logging, and retraining workflows. Experience working with MLOps/experiment tracking and operational tools (e.g., MLflow, Weights & Biases). Show more Show less

A career in our Advisory Acceleration Centre is the natural extension of PwC’s leading class global delivery capabilities. We provide premium, cost effective, high quality services that support process quality and delivery capability in support for client engagements. To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be an authentic and inclusive leader, at all grades/levels and in all lines of service. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future. Responsibilities As a Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: Use feedback and reflection to develop self awareness, personal strengths and address development areas. Delegate to others to provide stretch opportunities and coach to help deliver results. Develop new ideas and propose innovative solutions to problems. Use a broad range of tools and techniques to extract insights from from current trends in business area. Review your work and that of others for quality, accuracy and relevance. Share relevant thought leadership. Use straightforward communication, in a structured way, when influencing others. Able to read situations and modify behavior to build quality, diverse relationships. Uphold the firm's code of ethics and business conduct. The Opportunity When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills Edu qualifications: BE / B Tech / MCA/ MTech Experience range: 2 - 5 years Skill - GW Testing - Associate Job Description - Reviewing requirements / specifications / technical design documents Designing detailed, comprehensive and well-structured Test Plans and Test Cases Setting up Test Environment & Test Data Executing tests as needed throughout the project. Analyzing and reporting test results. Identifying and tracking defects through their lifecycle. Understanding of Integration - Technical Design Document and Use Case Testing experience of any one of the Guidewire products: PolicyCenter Experience on policy transactions, workflow ,Audits, forms inference Performing thorough testing [Smoke / System / Integration / Regression / Stabilization Possessing expertise in Test Management Tools like ALM / Jira Show more Show less

Summary We are seeking a Machine Learning Analyst with a strong foundation in Engineering or a related Quantitative Sciences discipline. While prior experience in Machine Learning is not mandatory, candidates with exposure to Machine Learning and Deep Learning (if any) are expected to demonstrate a rigorous understanding of the concepts they are familiar with. The ideal candidate must be a quick learner and demonstrate strong analytical skills, clear thinking and structured problem-solving, strong quantitative aptitude, a willingness to learn, high self-motivation, and a diligent work ethic. About Us Wadhwani AI is a nonprofit institute building and deploying applied AI solutions to solve critical issues in public health, agriculture, education, and urban development in underserved communities in the global south. We collaborate with governments, social sector organizations, academic and research institutions, and domain experts to identify real-world problems, and develop practical AI solutions to tackle these issues with the aim of making a substantial positive impact. We have over 30+ AI projects supported by leading philanthropies such as Bill & Melinda Gates Foundation and Google.org. With a team of over 200 professionals, our expertise encompasses AI/ML research and innovation, software engineering, domain knowledge, design and user research. In the Press: Our Founder Donors are among the Top 100 AI Influencers G20 India’s Presidency: AI Healthcare, Agriculture, & Education Solutions Showcased Globally. Unlocking the potentials of AI in Public Health Wadhwani AI Takes an Impact-First Approach to Applying Artificial Intelligence - data.org Winner of the H&M Foundation Global Change Award 2022 Indian Winners of the 2019 Google AI Impact Challenge, and the first in the Asia Pacific to host Google Fellow PRE-REQUISITES ML Analyst position is open to all with prior training in Engineering or any related Quantitative Sciences discipline No prior experience in Machine Learning or Deep Learning is required Candidates with exposure to ML/DL (if any) are expected to have a clear and rigorous understanding of the concepts they are familiar with Strong skills in data handling, and logical problem-solving Demonstrates a quick learning ability, and a strong work ethic Willingness to take on any task, learn new tools, and adapt to evolving project needs Roles & Responsibilities Work closely with data to support the development of ML and DL solutions Conduct experiments under guidance and report results reliably Learn to derive insights from experimental outcomes and determine appropriate next steps Prepare, curate, and analyse datasets for training and evaluation Monitor incoming data streams and perform regular quality checks Assist in training and inference of ML models, including deep learning architectures Contribute to well-documented and maintainable codebases Document work clearly and consistently with high standards Communicate and present experimental findings and results clearly within the team Learn and apply best practices across ML development, coding, documentation, and experimentation Collaborate effectively with project teams to meet milestones and deliverables Proactively seek help and feedback when needed Work efficiently with tools like Unix, VS Code, GitHub, and Docker Develop proficiency with common ML tools and libraries such as Pandas, Scikit-learn, PyTorch, Excel (pivot tables), Matplotlib, Weights & Biases DESIRED COMPETENSIES Demonstrates curiosity, humility, and a strong motivation to learn and grow Takes full ownership of tasks; highly diligent, detail-oriented, and accountable Willing to engage in all types of work from data cleaning and exploration to debugging and tooling Comfortable sitting with raw data to explore, understand and derive insights, and not just focused on modelling Proactively seeks guidance and independently builds knowledge when needed Approaches every task with a quality-first mindset; no task is considered beneath them Identifies recurring patterns and abstracts them into reusable, generalisable workflows Contributes across the entire ML lifecycle including data preparation, experimentation, and analysis Selects and applies appropriate tools; builds efficient, reliable, and repeatable processes Maintains a high standard of error-free work; reviews and validates work thoroughly Collaborates effectively with cross-functional teams Communicates clearly and constructively, with an emphasis on precision and clarity We are committed to promoting diversity and the principle of equal employment opportunity for all our employees and encourage qualified candidates to apply irrespective of religion or belief, ethnic or social background, gender, gender identity, and disability. If you have any questions, please email us at careers@wadhwaniai.org. Show more Show less

Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job: As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio. We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios. Responsibilities : Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint. Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms. Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions. Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems. Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements. A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms. A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios. Must have strong expertise in writing CPU and GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required. Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency. Show more Show less

About Us As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. At Target, we have a timeless purpose and a proven strategy and that hasn’t happened by accident. Some of the best minds from diverse backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values diverse backgrounds. We believe your unique perspective is important, and you'll build relationships by being authentic and respectful. At Target, inclusion is part of the core value. We aim to create equitable experiences for all, regardless of their dimensions of difference. As an equal opportunity employer, Target provides diverse opportunities for everyone to grow and win Behind one of the world’s best loved brands is a uniquely capable and brilliant team of data scientists, engineers and analysts. The Target Data & Analytics team creates the tools and data products to sustainably educate and enable our business partners to make great data-based decisions at Target. We help develop the technology that personalizes the guest experience, from product recommendations to relevant ad content. We’re also the source of the data and analytics behind Target’s Internet of Things (iOT) applications, fraud detection, Supply Chain optimization and demand forecasting. We play a key role in identifying the test-and-measure or A/B test opportunities that continuously help Target improve the guest experience, whether they love to shop in stores or at Target.com. About This Career Role is about being passionate about data, analysis, metrics development, feature experimentation and its application to improve both business strategies, as well as support to GSCL operations team Develop, model and apply analytical best practices while upskilling and coaching others on new and emerging technologies to raise the bar for performance in analysis by sharing with others (clients, peers, etc.) well documented analytical solutions . Drive a continuous improvement mindset by seeking out new ways to solve problems through formal trainings, peer interactions and industry publications to continually improve technically, implement best practices and analytical acumen Be expert in specific business domain, self-directed and drive execution towards outcomes, understand business inter-dependencies, conduct detailed problem solving, remediate obstacles, use independent judgement and decision making to deliver as per product scope, provide inputs to establish product/ project timelines Participate in learning forums, or be a buddy to help increase awareness and adoption of current technical topics relevant for analytics competency e.g. Tools (R, Python); exploratory & descriptive techniques ( basic statistics and modelling) Champion participation in internal meetups, hackathons; presents in internal conferences, relevant to analytics competency Contribute the evaluation and design of relevant technical guides and tools to hire great talent by partnering with talent acquisition Participate in Agile ceremonies to keep the team up-to-date on task progress, as needed Develop and analyse data reports/Dashboards/pipelines, do RCA and troubleshooting of issues that arise using exploratory and systemic techniques About You B.E/B.Tech (2-3 years of relevant exp), M.Tech, M.Sc. , MCA (+2 years of relevant exp) Candidates with strong domain knowledge and relevant experience in Supply Chain / Retails analytics would be highly preferred Strong data understanding inference of patterns, root cause, statistical analysis, understanding forecasting/predictive modelling, , etc. Advanced SQL experience writing complex queries Hands on experience with analytics tools: Hadoop, Hive, Spark, Python, R, Domo and/or equivalent technologies Experience working with Product teams and business leaders to develop product roadmaps and feature development Able to support conclusions with analytical evidence using descriptive stats, inferential stats and data visualizations Strong analytical, problem solving, and conceptual skills. Demonstrated ability to work with ambiguous problem definitions, recognize dependencies and deliver impact solutions through logical problem solving and technical ideations Excellent communication skills with the ability to speak to both business and technical teams, and translate ideas between them Intellectually curious, high energy and a strong work ethic Comfort with ambiguity and open-ended problems in support of supply chain operations Useful Links- Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Show more Show less

Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job: As a member of our AI model team, you will drive innovation across the entire AI lifecycle by developing and implementing rigorous evaluation frameworks and benchmark methodologies for pre-training, post-training, and inference. Your work will focus on designing metrics and assessment strategies that ensure our models are highly responsive, efficient, and reliable across real-world applications. You will work on a wide spectrum of systems, from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate text, images, and audio. We expect you to have deep expertise in advanced model architectures, pre-training and post-training practices, and inference evaluation frameworks. Adopting a hands-on, research-driven approach, you will develop, test, and implement novel evaluation strategies that rigorously track key performance indicators such as accuracy, latency, throughput, and memory footprint. Your evaluations will not only benchmark model performance at each stage, from the foundational pre-training phase to targeted post-training refinements and final inference but will also provide actionable insights. A key element of this role is collaborating with cross-functional teams including product management, engineering, and operations to share your evaluation findings and integrate stakeholder feedback. You will engineer robust evaluation pipelines and performance dashboards that serve as a common reference point for all stakeholders, ensuring that the insights drive continuous improvement in model deployment strategies. The ultimate goal is to set industry-leading standards for AI model quality and reliability, delivering scalable performance and tangible value in dynamic, real-world scenarios. Responsibilities : Develop, test, and deploy integrated frameworks that rigorously assess models during pre-training, post-training, and inference. Define and track key performance indicators such as accuracy, loss metrics, latency, throughput, and memory footprint across diverse deployment scenarios. Curate high-quality evaluation datasets and design standardized benchmarks to reliably measure model quality and robustness. Ensure that these benchmarks accurately reflect improvements achieved through both pre-training and post-training processes, and drive consistency in evaluation practices. Engage with product management, engineering, data science, and operations teams to align evaluation metrics with business objectives. Present evaluation findings, actionable insights, and recommendations through comprehensive dashboards and reports that support decision-making across functions. Systematically analyze evaluation data to identify and resolve bottlenecks across the model lifecycle. Propose and implement optimizations that enhance model performance, scalability, and resource utilization on resource-constrained platforms, ensuring efficient pre-training, post-training, and inference. Conduct iterative experiments and empirical research to refine evaluation methodologies, staying abreast of emerging techniques and trends. Leverage insights to continuously enhance benchmarking practices and improve overall model reliability, ensuring that all stages of the model lifecycle deliver measurable value in real-world applications. A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Demonstrated experience in designing and evaluating AI models at multiple stages from pre-training, post-training, and inference. You should be proficient in developing evaluation frameworks that rigorously assess accuracy, convergence, loss improvements, and overall model robustness, ensuring each stage of the AI lifecycle delivers measurable real-world value. Strong programming skills and hands-on expertise in evaluation benchmarks and frameworks are essential. Familiarity with building, automating, and scaling complex evaluation and benchmarking pipelines, and experience with performance metrics: latency, throughput, and memory footprint. Proven ability to conduct iterative experiments and empirical research that drive the continuous refinement of evaluation methodologies. You should be adept at staying abreast of emerging trends and techniques, leveraging insights to enhance benchmarking practices and model reliability. Demonstrated experience collaborating with diverse teams such as product, engineering, and operations in order to align evaluation strategies with organizational goals. You must be skilled at translating technical findings into actionable insights for stakeholders and driving process improvements across the model development lifecycle. Show more Show less

Appnext offers end-to-end discovery solutions covering all the touchpoints users have with their devices. Thanks to Appnext’s direct partnerships with top OEM brands and carriers, user engagement is achieved from the moment they personalize their device for the first time and throughout their daily mobile journey. Appnext ‘Timeline’, a patented behavioral analytics technology, is uniquely capable of predicting the apps users are likely to need next. This innovative solution means app developers and marketers can seamlessly engage with users directly on their smartphones through personalized, contextual recommendations. Established in 2012 and now with 12 offices globally, Appnext is the fastest-growing and largest independent mobile discovery platform in emerging markets. As a Machine Learning Engineer , you will be in charge of building end-to-end machine learning pipelines that operate at a huge scale, from data investigation, ingestions and model training to deployment, monitoring, and continuous optimization. You will ensure that each pipeline delivers measurable impact through experimentation, high-throughput inference, and seamless integration with business-critical systems. This job combines 70% machine learning engineering and 30% algorithm engineering and data science. We're seeking an Adtech pro who thrives in a team environment, possesses exceptional communication and analytical skills, and can navigate high-pressure demands of delivering results, taking ownership, and leveraging sales opportunities. Responsibilities: Build ML pipelines that train on real big data and perform on a massive scale. Handle a massive responsibility, Advertise on lucrative placement (Samsung appstore, Xiaomi phones, TrueCaller). Train models that will make billions of daily predictions and affect hundreds of millions users. Optimize and discover the best solution algorithm to data problems, from implementing exotic losses to efficient grid search. Validate and test everything. Every step should be measured and chosen via AB testing. Use of observability tools. Own your experiments and your pipelines. Be Frugal. Optimize the business solution at minimal cost. Advocate for AI. Be the voice of data science and machine learning, answering business needs. Build future products involving agentic AI and data science. Affect millions of users every instant and handle massive scale Requirements: MSc in CS/EE/STEM with at least 5 years of proven experience (or BSc with equivalent experience) as a Machine Learning Engineer: strong focus on MLOps, data analytics, software engineering, and applied data science- Must Hyper communicator: Ability to work with minimal supervision and maximal transparency. Must understand requirements rigorously, while frequently giving an efficient honest picture of his/hers work progress and results. Flawless verbal English- Must Strong problem-solving skills, drive projects from concept to production, working incrementally and smart. Ability to own features end-to-end, theory, implementation, and measurement. Articulate data-driven communication is also a must. Deep understanding of machine learning, including the internals of all important ML models and ML methodologies. Strong real experience in Python, and at least one other programming language (C#, C++, Java, Go…). Ability to write efficient, clear, and resilient production-grade code. Flawless in SQL. Strong background in probability and statistics. Experience with tools and ML models Experience with conducting A/B test. Experience with using cloud providers and services (AWS) and python frameworks: TensorFlow/PyTorch, Numpy, Pandas, SKLearn (Airflow, MLflow, Transformers, ONNX, Kafka are a plus). AI/LLMs assistance: Candidates have to hold all skills independently without using AI assist. With that candidates are expected to use AI effectively, safely and transparently. Preferred: Deep Knowledge in ML aspects including ML Theory, Optimization, Deep learning tinkering, RL, Uncertainty quantification, NLP, classical machine learning, performance measurement. Prompt engineering and Agentic workflows experience Web development skills Publication in leading machine learning conferences and/or medium blogs. Show more Show less

We are looking for an experienced Machine Learning Engineer with deep expertise in Computer Vision and Generative AI to join our team in New Delhi, India, and own the end-to-end development and improvement of various innovative problem statements. You will take full ownership of projects, from ideation to delivery, ensuring successful deployment as well as ML monitoring post-launch. Responsibilities Own the entire lifecycle of the Vision and GenAI problem statement, from initial concept throughout deployment. Research, design, develop, and deploy robust and scalable ML systems for various Vision use-cases. Optimize model training and inference pipelines to maximize GPU utilization and minimize costs. Collaborate with Product, Backend, and Platform teams to define project timelines, ensure alignment of business goals, and drive strong execution. Requirements Solid foundation in Deep Learning, Computer Vision, and Generative AI, with a proven experience of 4-6 years, preferably in a fast-paced startup environment. In-depth and practical knowledge of CNNs, GANs, VAEs, Diffusion models, and Inpainting methods, image processing techniques, text-to-image and image-to-image generation architectures, etc. Strong programming skills in Python and proficiency with ML frameworks (e., Tensorflow, Pytorch, JAX) - create code that is understandable, simple, clean, and easily shared with others. Experience in deploying Vision models on edge devices, optimizing for resource constraints. Knack for staying up to date with the latest research and trying out unconventional, out-of-the-box ideas. Passion for problem-solving and creative thinking, with the ability to break down complex and abstract problems into actionable items. Self-motivated to build, with an ability to thrive with minimal oversight and process. Bonus Points Experienced with 3D computer vision, video processing, and text-to-video, image-to-video generation. Knowledge of the Rust programming language for implementing the inference pipelines. Experienced working with highly skewed and imbalanced data. Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). This job was posted by Madhur Khake from Aftershoot. Show more Show less

This role is for one of Weekday's clients Salary range: Rs 2000000 - Rs 9000000 (ie INR 20-90 LPA) Min Experience: 4 years JobType: full-time Requirements What You'll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you'll help define what "good" looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You'll Need 2-3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques 1-2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda) Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they're truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You've built systems — not just prototypes You care about both ML results and the system's behavior in production You're comfortable taking a rough business goal and shaping the technical path to get there You're energized by product-focused AI work — things that users feel and rely on You've worked in or want to work in a startup-grade environment: messy, fast, and impactful What You Get Full autonomy over your problem space A builder-first, no-handoff culture Remote-first flexibility (India preferred) Base + Variable + meaningful equity A product shipping to some of the world's most recognizable brands Show more Show less