1801 Inference Jobs - Page 35

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

We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a strong background in designing, deploying, and maintaining advanced AI/ML models with expertise in Natural Language Processing (NLP), Computer Vision, and architectures like Transformers and Diffusion Models. You will play a key role in developing AI-powered solutions, optimizing performance, and deploying and managing models in production environments. Key Responsibilities AI Model Development and Optimization: Design, train, and fine-tune AI models for NLP, Computer Vision, and other domains using frameworks like TensorFlow and PyTorch. Work on advanced architectures, including Transformer-based models (e.g., BERT, GPT, T5) for NLP tasks and CNN-based models (e.g., YOLO, VGG, ResNet) for Computer Vision applications. Utilize techniques like PEFT (Parameter-Efficient Fine-Tuning) and SFT (Supervised Fine-Tuning) to optimize models for specific tasks. Build and train RLHF (Reinforcement Learning with Human Feedback) and RL-based models to align AI behavior with real-world objectives., Explore multimodal AI solutions combining text, vision, and audio using generative deep learning architectures. Natural Language Processing (NLP): Develop and deploy NLP solutions, including language models, text generation, sentiment analysis, and text-to-speech systems. Leverage advanced Transformer architectures (e.g., BERT, GPT, T5) for NLP tasks. AI Model Deployment and Frameworks: Deploy AI models using frameworks like VLLM, Docker, and MLFlow in production-grade environments. Create robust data pipelines for training, testing, and inference workflows. Implement CI/CD pipelines for seamless integration and deployment of AI solutions. Production Environment Management: Deploy, monitor, and manage AI models in production, ensuring performance, reliability, and scalability. Set up monitoring systems using Prometheus to track metrics like latency, throughput, and model drift. Data Engineering and Pipelines: Design and implement efficient data pipelines for preprocessing, cleaning, and transformation of large datasets. Integrate with cloud-based data storage and retrieval systems for seamless AI workflows. Performance Monitoring and Optimization: Optimize AI model performance through hyperparameter tuning and algorithmic improvements. Monitor performance using tools like Prometheus, tracking key metrics (e.g., latency, accuracy, model drift, error rates etc.) Solution Design and Architecture: Collaborate with cross-functional teams to understand business requirements and translate them into scalable, efficient AI/ML solutions. Design end-to-end AI systems, including data pipelines, model training workflows, and deployment architectures, ensuring alignment with business objectives and technical constraints. Conduct feasibility studies and proof-of-concepts (PoCs) for emerging technologies to evaluate their applicability to specific use cases. Stakeholder Engagement: Act as the technical point of contact for AI/ML projects, managing expectations and aligning deliverables with timelines. Participate in workshops, demos, and client discussions to showcase AI capabilities and align solutions with client needs. Experience: 2 - 6 years of experience Salary : 5-11 LPA Job Types: Full-time, Permanent Pay: ₹500,000.00 - ₹1,100,000.00 per year Schedule: Day shift Work Location: In person

Job Information Date Opened 06/16/2025 Job Type Full time Industry IT Services Work Experience 3+ Years Salary 8-15 LPA City Mohali State/Province Punjab Country India Zip/Postal Code 160071 Job Description ABOUT XENONSTACK XenonStack is the fastest-growing data and AI foundry for agentic systems, which enables people and organizations to gain real-time and intelligent business insights. Building Agentic Systems for AI Agents with https://www.akira.ai Vision AI Platform with https://www.xenonstack.ai Inference AI Infrastructure for Agentic Systems - https://www.nexastack.ai THE OPPORTUNITY We are seeking an experienced DevOps Engineer with 3-6 years of experience in implementing and reviewing CI/CD pipelines, cloud deployments, and automation tasks. If you have a strong foundation in cloud technologies, containerization, and DevOps best practices, we would love to have you on our team. JOB ROLES AND RESPONSIBILITIES Develop and maintain CI/CD pipelines to automate the deployment and testing of applications across AWS and Private Cloud. Assist in deploying applications and services to cloud environments while ensuring optimal configuration and security practices. Implement monitoring solutions to ensure infrastructure health and performance; troubleshoot issues as they arise in production environments. Automate repetitive tasks and manage cloud infrastructure using tools like Terraform, CloudFormation, and scripting languages (Python, Bash). Work closely with software engineers to integrate deployment pipelines with application codebases and streamline workflows. Ensure efficient resource management in the cloud, monitor costs, and optimize usage to reduce waste. Create detailed documentation for DevOps processes, deployment procedures, and troubleshooting steps to ensure clarity and consistency across the team. Requirements SKILLS REQUIREMENTS 2-4 years of experience in DevOps or cloud infrastructure engineering. Proficiency in cloud platforms on AWS, and hands-on experience with their core services (EC2, S3, RDS, Lambda, etc.). Advanced knowledge of CI/CD tools such as Jenkins, GitLab CI, or CircleCI, and hands-on experience implementing and managing CI/CD pipelines. Experience with containerization technologies like Docker and Kubernetes for deploying applications at scale. Strong knowledge of Infrastructure-as-Code (IaC) using tools like Terraform or CloudFormation. Proficient in scripting languages such as Python and Bash for automating infrastructure tasks and deployments. Understanding of monitoring and logging tools like Prometheus, Grafana, ELK Stack, or CloudWatch to ensure system performance and uptime. Strong understanding of Linux-based operating systems and cloud-based infrastructure management. Bachelor’s degree in Computer Science, Information Technology, or related field. Benefits CAREER GROWTH AND BENEFITS Continuous Learning & Growth Access to training, certifications, and hands-on sessions to enhance your DevOps and cloud engineering skills. Opportunities for career advancement and leadership roles in DevOps engineering. Recognition & Rewards Performance-based incentives and regular feedback to help you grow in your career. Special recognition for contributions towards streamlining and improving DevOps practices. Work Benefits & Well-Being Comprehensive health insurance and wellness programs to ensure a healthy work-life balance. Cab facilities for women employees and additional allowances for project-based tasks. XENONSTACK CULTURE - JOIN US & MAKE AN IMPACT Here at XenonStack, we have a culture of cultivation with bold, courageous, and human-centric leadership principles. We value obsession and deep work in everything we do. We are on a mission to disrupt and reshape the category and welcome people with that mindset and ambition. If you are energised by the idea of shaping the future of AI in Business processes and enterprise systems, there’s nowhere better for you than XenonStack Product Value and Outcome - Simplifying the user experience with AI Agents and Agentic AI 1) Obsessed with Adoption : We design everything with the goal of making AI more accessible and simplifying the business processes and enterprise systems essential to adoption. 2) Obsessed with Simplicity : We simplify even the most complex challenges to create seamless, intuitive experiences with AI agents and Agentic AI. Be a part of XenonStack’s Vision and Mission for Accelerating the world's transition to AI + Human Intelligence.

Job Details Job Description: Develops algorithms and applications, performs large scale experimentation, builds data driven apps to translate data into intelligence, and develops solutions for solving business problems using coding. Incorporates predictive modeling, statistics and other analysis techniques for collecting, exploring, interpreting and extracting insights from structured and unstructured data. Organizes, interprets and structures insights from data, detects data anomalies and makes corrections. Performs descriptive statistical analysis, develops visualizations, applications, dashboards, or presentations and communicates insights in a clear and effective way to help the organization with better decisionmaking. Supports troubleshooting service offerings using proprietary analytical platforms, commercial tools and custom scripts. Drives the design, development and optimization of artificial intelligence/machine learning, deep learning training and inference frameworks, contributes to the research and development of data science activities and supports product development efforts as required. Develops and programs methods, processes, and systems to consolidate and analyze diverse big data sources, establishing standard methodologies for data science including modeling, coding, analytics, and experimentation. Explores, compiles, and collects data from new or known sources, sometimes in partnership with technical staff/engineers to derive useful insights and/or make predictions. Works with development teams and business units to ensure models are scalable and can be implemented as part of the delivered solution across clients. Qualifications M Tech Computer Science Job Type Student / Intern Shift Shift 1 (India) Primary Location: India, Bangalore Additional Locations: Business Group As members of the Finance team, employees act as full partners in making and supporting business decisions that are aimed at maximizing shareholder value. Intel Finance has a strong focus on facilitating change and improvement both within finance and in the operations supported. Posting Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Position of Trust N/A Work Model for this Role This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change. Legal Disclaimer It has come to our notice that some people have received fake job interview letters ostensibly issued by Intel, inviting them to attend interviews in Intel’s offices for various positions and further requiring them to deposit money to be eligible for the interviews. We wish to bring to your notice that these letters are not issued by Intel or any of its authorized representatives. Hiring at Intel is based purely on merit and Intel does not ask or require candidates to deposit any money. We would urge people interested in working for Intel, to apply directly at https://jobs.intel.com/ and not fall prey to unscrupulous elements. Show more Show less

Company Description At Applus IDIADA we are looking for talent to help us shape the mobility of tomorrow with safer, more efficient and sustainable vehicles. With presence in 22 countries, we offer job positions around the world and within the company. The automotive sector is currently living a moment of deep technological change. At IDIADA, we focus on constant innovation to adapt our services’ portfolio to an ever-changing environment. Therefore, as part of our team, we expect you to be dynamic and eager to learn and grow with us. Job Description Manage, organise, plan and lead a team of expert testing & instrumentation engineers for successful fulfillment of project requirements for various clients in the domains of Vehicle Dynamics, Brakes, NVH testing and training services under the supervision of the Head of Chassis & Active Safety. Perform dynamic tests on proving grounds and public roads as required for passenger cars and light commercial vehicle's projects independently Perform dynamic test data analysis, mainly through in-house developed software's include pre/post processing of the experimental data to check the vehicle dynamics behavior of the tested vehicle and being able to explain the root of the phenomena happening independently. Demonstrate, present and justify technical decisions based on test & report data to internal teams & clients for vehicle attribute development under the guidance of the Head of Chassis & Active Safety. Manage client interaction, client project reporting and support with sales presentations under the supervision of the Head of Chassis & Active Safety. Ensure occupational health and safety and IDIADA quality process is adhered to at all times in the department under the guidance of the Head of Chassis & Active Safety. Train and develop a team of vehicle dynamics instrumentation and test engineers to meet IDIADA global testing standards and monitor skill matrix and technical competency development Qualifications A Bachelors Degree in Mechanical, Automotive Engineering or Mechatronics; Masters Degree an added benefit. Minimum 5 years of experience in chassis testing with excellent knowledge of vehicle dynamics subjective evaluation, objective testing, data analysis and or calibration of chassis systems A strong theoretical and practical knowledge of vehicle dynamics and automotive technology with an excellent mathematical background to perform post processing analysis and inference of test data. Good analytical and problem analysis and solving skills. Must posses excellent driving skills and vehicle motion feedback Must posses relevant PG license certification, advanced driver training certifications and LMV, LCV with badge, HTV an added advantage Dynamic, proactive, self-motivated, and passion to learn is a must. Willingness and ability to travel globally and locally when required on short notice Good communication skills, both verbal and written in English a must; Hindi and local Indian languages an added advantage Additional Information Applus IDIADA is committed to equality, diversity and inclusion . We don’t put limits on you, so don’t put limits on yourself either. There is a place for everyone.

Wipro Limited (NYSE: WIT, BSE: 507685, NSE: WIPRO) is a leading technology services and consulting company focused on building innovative solutions that address clients’ most complex digital transformation needs. Leveraging our holistic portfolio of capabilities in consulting, design, engineering, and operations, we help clients realize their boldest ambitions and build future-ready, sustainable businesses. With over 230,000 employees and business partners across 65 countries, we deliver on the promise of helping our customers, colleagues, and communities thrive in an ever-changing world. For additional information, visit us at www.wipro.com. Job Description Role Purpose The purpose of the role is to create exceptional architectural solution design and thought leadership and enable delivery teams to provide exceptional client engagement and satisfaction. ͏ Mandatory Skills Data Science, ML, DL, NLP or Computer Vision, Python, Tensorflow, Pytorch, Django, PostgreSQL Preferred Skills Gen AI, LLM, RAG, Lanchain, Vector DB, Azure Cloud, MLOps, Banking exposure ͏ 3.Competency Building and Branding Ensure completion of necessary trainings and certifications Develop Proof of Concepts (POCs),case studies, demos etc. for new growth areas based on market and customer research Develop and present a point of view of Wipro on solution design and architect by writing white papers, blogs etc. Attain market referencability and recognition through highest analyst rankings, client testimonials and partner credits Be the voice of Wipro’s Thought Leadership by speaking in forums (internal and external) Mentor developers, designers and Junior architects in the project for their further career development and enhancement Contribute to the architecture practice by conducting selection interviews etc ͏ Mandatory Strong understanding of Data Science, machine learning and deep learning principles and algorithms. Proficiency in programming languages such as Python, TensorFlow, and PyTorch. Ability to work with large datasets and knowledge of data preprocessing techniques. Strong Backend Python developer Experience in applying machine learning techniques, Natural Language Processing or Computer Vision using TensorFlow, Pytorch Build and deploy end to end ML models and leverage metrics to support predictions, recommendations, search, and growth strategies Expert in applying ML techniques such as: classification, clustering, deep learning, optimization methods, supervised and unsupervised techniques Optimize model performance and scalability for real-time inference and deployment. Experiment with different hyperparameters and model configurations to improve AI model quality. Ensure AI ML solutions are developed, and validations are performed in accordance with Responsible AI guidelines. ͏ 4.Team Management Resourcing Anticipating new talent requirements as per the market/ industry trends or client requirements Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Mandatory Skills: Generative AI. Experience: 8-10 Years. Reinvent your world. We are building a modern Wipro. We are an end-to-end digital transformation partner with the boldest ambitions. To realize them, we need people inspired by reinvention. Of yourself, your career, and your skills. We want to see the constant evolution of our business and our industry. It has always been in our DNA - as the world around us changes, so do we. Join a business powered by purpose and a place that empowers you to design your own reinvention. Come to Wipro. Realize your ambitions. Applications from people with disabilities are explicitly welcome.

You Lead the Way. We’ve Got Your Back. With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally. At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong. Join Team Amex and let's lead the way together. How will you make an impact in this role? Manage and Lead the Discovery, Development and Maintenance of scalable AI/ML and Gen-AI driven capabilities in the area of Document AI, Computer Vision, NLP, Chatbots (Conversational AI). Direct and lead the Research and Deployment of AI and Gen-AI solutions to power enterprise business needs Analyzes business requirements and directs the translation into AI/machine learning-driven technical solutions, evaluating business needs and guiding the development of models and solutions Deliver scalable AI solutions, managing interdisciplinary teams to meet business and technical requirements Create data pipelines that feed machine learning models throughout the model lifecycle including training, inference ,HITL and re-training . Closely follow research and open-source developments/publications and apply them. Drive high-level and detailed technical design conversations and reviews Function as an active member of an agile team Minimum Qualifications BS or MS degree in computer science, computer engineering, or other technical discipline. Strong proficiency in Python language, machine learning libraries and SQL Core competencies in distributed technologies including Python frameworks, API Design, Linux, JSON, Postgres, NoSQL databases etc. Demonstrated experience in building and deploying a diverse set of ML models including vision and NLP based models at scale Experience in designing and implementing highly scalable, low latency Python applications. Familiarity with CI/CD pipelines and DevOps tools (Jenkins, GitLab). Proficiency with Containers (Docker) and orchestration (Airflow, Kubernetes) Practical knowledge of caching and distributed systems. Team player and a hands-on engineer. Have excellent written and verbal communications skills. Preferred Qualifications 8+ years of software development experience Experience leading a small group of engineers in a lead role Hands-on experience in GCP/AWS/Azure cloud is a preferred Experience in Financial Services industry is a plus We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.