1773 Inference Jobs - Page 23

Responsibilities: Deploy, scale, and manage large language models (LLMs) in production environments, ensuring optimal resource usage and performance. Design, implement, and manage CI/CD pipelines to automate the software delivery process, ensuring fast and reliable deployments. Monitor and analyze model performance in real-time, addressing issues like model drift, latency, and accuracy degradation, and initiating model retraining or adjustments when necessary. Manage cloud environments (AWS, GCP, Azure etc.,) to provision and scale infrastructure to meet the needs of training, fine-tuning, and inference for large models. Collaborate with development teams to integrate CI/CD pipelines into the development workflow, promoting continuous integration and delivery best practices. Implement infrastructure as code (IaC) using tools such as Terraform, Ansible, or CloudFormation to automate the provisioning and management of infrastructure. Manage and maintain cloud infrastructure on platforms such as AWS, Azure, or Google Cloud, ensuring scalability, security, and reliability. Develop and implement monitoring, logging, and alerting solutions to ensure the health and performance of applications and infrastructure. Work closely with security teams to integrate security practices into the CI/CD pipelines, ensuring compliance with industry standards and regulations. Optimize build and release processes to improve efficiency and reduce deployment times, implementing strategies such as parallel builds and incremental deployments. Automate testing processes within the CI/CD pipelines to ensure high-quality software releases, including unit tests, integration tests, and performance tests. Manage and monitor version control systems, such as Git, to ensure code integrity and facilitate collaboration among development teams. Provide technical support and troubleshooting for CI/CD-related issues, ensuring timely resolution and minimal disruption to development workflows. Develop and maintain documentation for CI/CD pipelines, infrastructure configurations, and best practices, ensuring clarity and accessibility for team members. Stay updated on the latest trends and advancements in DevOps, CI/CD, and cloud computing, and incorporate new tools and practices into the organization's workflows. Lead and participate in code reviews and technical discussions, providing insights and recommendations for continuous improvement. Conduct training sessions and workshops for internal teams to promote knowledge sharing and best practices in DevOps and CI/CD. Collaborate with IT and development teams to implement and manage containerization solutions using Docker and orchestration platforms such as Kubernetes. Implement and manage configuration management solutions to maintain consistency and manage changes across environments. Develop and implement disaster recovery and business continuity plans to ensure the resilience and availability of applications and infrastructure. Optimize resource utilization and cost management for cloud infrastructure, implementing strategies such as auto-scaling and resource tagging. Facilitate communication between development, operations, and business stakeholders to ensure alignment on DevOps goals and practices. Participate in the evaluation and selection of DevOps tools and technologies that align with organizational goals and improve software delivery processes. Manage and monitor application performance, implementing strategies to optimize performance and resolve bottlenecks. Ensure compliance with organizational policies and industry regulations related to software development and deployment. Required Skills: Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Extensive experience in DevOps practices and CI/CD implementation. Strong proficiency in CI/CD tools such as Jenkins, GitLab CI, or CircleCI. Experience with cloud platforms such as AWS, Azure, or Google Cloud. Proficiency in infrastructure as code (IaC) tools such as Terraform, Ansible, or CloudFormation. Strong understanding of containerization and orchestration platforms such as Docker and Kubernetes. Experience with monitoring, logging, and alerting tools such as Prometheus, Grafana, ELK Stack, or Datadog. Proficiency in scripting languages such as Python, Bash, or PowerShell. Strong understanding of version control systems such as Git. Excellent problem-solving and analytical skills, with the ability to troubleshoot and resolve technical issues. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders. Certification in DevOps or cloud platforms (e.g., AWS Certified DevOps Engineer, Azure DevOps Engineer Expert) is preferred. Preferred Skills: Experience with monitoring, logging, and alerting tools such as Prometheus, Grafana, ELK Stack, or Datadog. Proficiency in scripting languages such as Python, Bash, or PowerShell. Strong understanding of version control systems such as Git. Excellent problem-solving and analytical skills, with the ability to troubleshoot and resolve technical issues. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders. Certification in DevOps or cloud platforms (e.g., AWS Certified DevOps Engineer, Azure DevOps Engineer Expert) is preferred.

Responsibilities Build multi-agent systems capable of reasoning, tool use, and autonomous action Implement Model Context Protocol (MCP) strategies to manage complex, multi-source context Integrate third-party APIs (e.g., Crunchbase, PitchBook, CB Insights), scraping APIs, and data aggregators Develop browser-based agents enhanced with computer vision for dynamic research, scraping, and web interaction Optimize inference pipelines, task planning, and system performance Collaborate on architecture, prototyping, and iterative development Experiment with prompt chaining, tool calling, embeddings, and vector search Requirements 5+ years of experience in software engineering or AI/ML development Strong Python skills and experience with LangChain, LlamaIndex, or agentic frameworks Proven experience with multi-agent systems, tool calling, or task planning agents Familiarity with Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and multi-modal context handling Experience with browser automation frameworks (e.g., Playwright, Puppeteer, Selenium) Cloud deployment and systems engineering experience (GCP, AWS, etc.) Self-starter attitude with strong product sense and iteration speed Bonus Points Experience with AutoGen, CrewAI, OpenAgents, or ReAct-style frameworks Background in building AI systems that blend structured and unstructured data Experience working in a fast-paced startup environment Previous startup or technical founding team experience

NPS Prism Title: Senior Data Scientist, NPS Prism Last updated: June 2025 Company Profile: NPS Prism is a market-leading, cloud-based CX benchmarking and operational improvement platform owned by Bain & Company. NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences. Based on rock-solid sampling, research, and analytic methodology, it lets customers see how they compare to their competitors on overall NPS®, and on every step of the customer journey. With NPS Prism you can see where you’re strong, where you lag, and how customers feel about doing business with you and your competitors, in their own words. The result: Prioritize the customer interactions that matter most. NPS Prism customers use our customer experience benchmarks and insights to propel their growth and outpace the competition. Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world. NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a company consistently recognized as one of the world’s best places to work. We believe that diversity, inclusion and collaboration is key to building extraordinary teams. We hire people with exceptional talents, abilities and potential, then create an environment where you can become the best version of yourself and thrive both professionally and personally. Position Summary: NPS Prism has experienced tremendous growth as a standalone software and data business over the past few years and is making the leap from being a consulting-led business to a technology-led business. Given that shift, we are looking to build our team with world-class team members to help drive business growth to its full potential in this next phase. This is a great opportunity to help build the largest startup owned by Bain & Company and take NPS Prism into the future. Key Responsibilities: Act as a mentor, guiding and coaching junior Data Scientists in technical and storytelling aspects Lead the development, deployment, and adoption of open source LLM models to do text classification, building sentiment models Lead the development, deployment, and adoption of causal inference models to measure marketing campaigns, optimizing investments across short and long-term business objectives Collaborate with Data Engineering, Product and Technology teams on further build out of analytics architecture Take ownership of end-to-end projects, operating where there's a high degree of ambiguity, and delivering results within ambitious timelines Translate insights into relevant business recommendations, anticipating the needs of business stakeholders Research prior work to inform and develop models and algorithms and quantify appropriate metrics & targets Required Qualifications, Experience & Skills Education Bachelor's degree in computer science or Equivalent experience Experience 6 to 10 years Data Science experience covering ML, DL and GenAI 2+ years of experience building end-to-end data science applications using dash, Flask, Streamlit and Django etc. (Preferred) Skills Experience with building end-to-end data science applications Experience with NLP and LLMfine tuning Experience with cultural transformation to CI/CD and MLOps Experience with Azure MLOps or other SDLC tools Experience with Agile methodologies Experience building applications using fast APIs Experience in a start-up, fast-growth, rapid-change environment Must be self-motivated, dedicated to quality and must always strive to “do the right thing” Preferred Qualifications: Experience with HTML, CSS, JavaScript, version control using Git Experience with Containers and Kubernetes Experience with TensorFlow, Pytorch etc Powered by JazzHR yPQ1ufIEcf

Date: 20 Jun 2025 Location: Bangalore, KA, IN, 560099 Custom Field 1: Discovery Services Job Title: Bioinformatician Job Location: Bangalore About Syngene: Syngene ( www.syngeneintl.com ) is an innovation-led contract research, development and manufacturing organization offering integrated scientific services from early discovery to commercial supply. At Syngene, safety is at the heart of everything we do personally and professionally. Syngene has placed safety at par with business performance with shared responsibility and accountability, including following safety guidelines, procedures, and SOPs, in letter and spirit Overall adherence to safe practices and procedures of oneself and the teams aligned Contributing to development of procedures, practices and systems that ensures safe operations and compliance to company’s integrity & quality standards Driving a corporate culture that promotes environment, health, and safety (EHS) mindset and operational discipline at the workplace at all times. Ensuring safety of self, teams, and lab/plant by adhering to safety protocols and following environment, health, and safety (EHS) requirements at all times in the workplace. Ensure all assigned mandatory trainings related to data integrity, health, and safety measures are completed on time by all members of the team including self Compliance to Syngene’ s quality standards at all times Hold self and their teams accountable for the achievement of safety goals Govern and Review safety metrics from time to time We are seeking a highly skilled and experienced computational biologist to join our team. The ideal candidate will have a proven track record in multi-omics data analysis. They will be responsible for integrative analyses and contributing to the development of novel computational approaches to uncover biological insights. Experience: 1-4 years Core Purpose of the Role To support data-driven biological research by performing computational analysis of omics data, and generating translational insights through bioinformatics tools and pipelines. Position Responsibilities Conduct comprehensive analyses of multi-omics datasets, including genomics, transcriptomics, proteomics, metabolomics, and epigenomics. Develop computational workflows to integrate various -omics data to generate inference and hypotheses for testing. Conduct differential expression and functional enrichment analyses. Implement and execute data processing workflows and automate the pipelines with best practices for version control, modularization, and documentation. Apply advanced multivariate data analysis techniques, including regression, clustering, and dimensionality reduction, to uncover patterns and relationships in large datasets. Collaborate with researchers, scientists, and other team members to translate computational findings into actionable biological insights. Educational Qualifications Master’s degree in bioinformatics. Mandatory Technical Skills Programming: Proficiency in Python for data analysis, visualization, and pipeline development. Multi-omics analysis: Proven experience in analyzing and integrating multi-omics datasets. Statistics: Knowledge of probability distributions, correlation analysis, and hypothesis testing. Data visualization: Strong understanding of data visualization techniques and tools (e.g., ggplot2, matplotlib, seaborn). Preferred Machine learning: Familiarity with AI/ML concepts Behavioral Skills Excellent communication skills Objective thinking Problem solving Proactivity Syngene Values All employees will consistently demonstrate alignment with our core values Excellence Integrity Professionalism Equal Opportunity Employer It is the policy of Syngene to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by applicable legislation or local law. In addition, Syngene will provide reasonable accommodations for qualified individuals with disabilities.

Summary Understand complex and critical business problems from Country/Regional/Global business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to discover actionable insights and automate process for reducing effort and time for repeated use. High agility to be able to work across various business domains (commercial, NTO, GDD, NIBR, NBS) or divisions (Onco, GenMeds, Sandoz). Able to use business presentations, smart visualization tools and contextual storytelling to translate findings back to business users with a clear impact. No direct team management. About The Role Data Scientist I Location – Hyderabad Hybrid Major Accountabilities Work on a variety of business applications including but not limited to: Customer Segmentation & Targeting, Event Prediction, Propensity Modelling, Churn Modelling, Customer Lifetime Value Estimation, Forecasting, Recom-mender Systems, Modelling Response to Incentives, Marketing Mix Optimization, Price Optimization Develop automation for repeatedly refreshing analysis and generating insights Collaborates with globally dispersed internal stakeholders and cross-functional teams to solve critical business problems and deliver successfully on high visibility strategic initiatives Understand life science data sources including sales, contracting, promotions, social me-dia, patient claims and Real-World Evidence. Quickly learn the use of tools, data sources and analytical techniques needed to answer a wide range of critical business questions Articulate solutions/recommendations to business users. Works with senior data science team member to present analytical content concisely and effectively Manage own tasks and work with allied team members; plans proactively, anticipates and actively manages change, sets stakeholder expectations as required, identifies operational risks and independently drives issues to resolution, minimizes surprise escalations Independently identifies research articles and reproduce/apply methodology to Novartis business problems Has high learning agility and diligently follows updates in industry and area of work. Essential Requirements: Quality of insights generated, and solutions provided, with quantified business impact / ROI Effective communication with Country/Regional/Global stakeholders Executes agreed targets for self Define and execute development plans for potential Subject Matter Experts Find creative ways to build team capabilities and play a direct role in driving a culture of innovation Values and Behaviors: in line with leadership standards of Novartis Education: PhD or Masters (or bachelor’s from a top Tier University) in a quantitative discipline (e.g. Statistics, Economics, Mathematics, Computer Science, Bioinformatics, Ops Research, etc.)Experience: 7+ years of relevant experience in Data Science. In case of PhD, 4+ years post qualification experience. Experience in commercial pharma would be a bonus. Extensive experience required in: Statistical and Machine Learning techniques like Regression (esp., GLM, non-linear, etc.), Classification (CART, RF, SVM, GBM, etc.) Clustering, Design of Experiments, Monte Carlo Simulations, Statistical Inference, Feature Engineering, Time Series Forecasting, Text Mining and Natural Language Processing Good to have skills: Stochastic models, Bayesian Models, Markov Chains, Dynamic Programming and Optimization techniques, Deep Learning techniques on structured and un-structured data, Recommender Systems (content and collaborative filtering), etc. Tools and Packages: SAS, R, Python, SQL. Exposure to dashboard or web-apps building using Qliksense, R-Shiny, Flask, etc. would be an added advantage. Why Novartis: Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us! Learn more here: https://www.novartis.com/about/strategy/people-and-culture You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards Commitment To Diversity And Inclusion Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve. Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here: https://talentnetwork.novartis.com/network. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Opportunity Develop ML models, platforms, and services for Adobe Express as a Machine Learning Engineer. About The Team The AI Foundation Team at Adobe Express aims to develop a groundbreaking AI stack using internal and external technologies to improve feature speed and quality. Develop ML models and services, collaborate with teams, improve user experience at Adobe Express. What You'll Do 12+ Years of experience in the field Research, design, and implement advanced ML models and pipelines for training and inference at scale, including techniques in computer vision, NLP, deep learning, and generative AI. Integrate Large Language Models (LLMs) and agent-based frameworks to support multimodal creative workflows, enabling rich, context-aware content generation and dynamic user experiences. Collaborate with multi-functional teams to translate product requirements into ML solutions, iterating from proof-of-concept to fully productionized services. Develop robust platforms for continuous model training, experimentation, A/B testing, and monitoring, ensuring that model quality and relevance remain consistently high. Leverage distributed computing technologies and cloud infrastructures to handle large-scale data processing, feature engineering, and real-time inference, optimizing for performance and cost-efficiency. Implement reliable APIs and microservices that serve ML models to end users, ensuring alignment to standard methodologies in security, compliance, scalability, and maintainability. Stay ahead of emerging ML research, tools, and frameworks, evaluating and integrating new technologies such as sophisticated LLMs, reinforcement learning-based agents, and innovative inference optimization techniques. Basic Qualifications: PhD or Master’s or Bachelor's or equivalent experience in Computer Science, ML, Applied Mathematics, Data Science, or a related technical field. Proficiency in Python and Java for ML model development and systems integration. Hands-on experience with deep learning frameworks, including TensorFlow and PyTorch. Demonstrated experience working with LLMs and agent frameworks to develop advanced AI-based experiences. Proficiency in computer vision and NLP techniques for multimodal content understanding and generation. Work experience in Creative Domains, Imaging Domains will be highly useful. Experience in developing and deploying RESTful web services and microservices architectures for applications involving ML. Proficiency with UNIX environments, Git for version control, and Jenkins for CI/CD processes. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more about our vision here. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

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 Senior 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. Edu qualifications: BE / B Tech / MCA/ MTech Experience range: 5 - 10 years Skill - GW Testing - Senior 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

About Oportun Oportun (Nasdaq: OPRT) is a mission-driven fintech that puts its 2.0 million members' financial goals within reach. With intelligent borrowing, savings, and budgeting capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $16.6 billion in responsible and affordable credit, saved its members more than $2.4 billion in interest and fees, and helped its members save an average of more than $1,800 annually. Oportun has been certified as a Community Development Financial Institution (CDFI) since 2009. WORKING AT OPORTUN Working at Oportun means enjoying a differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture where we all feel a sense of belonging and are encouraged to share our perspectives. This inclusive culture is directly connected to our organization's performance and ability to fulfill our mission of delivering affordable credit to those left out of the financial mainstream. We celebrate and nurture our inclusive culture through our employee resource groups. Company Overview At Oportun, we are on a mission to foster financial inclusion for all by providing affordable and responsible lending solutions to underserved communities. As a purpose-driven financial technology company, we believe in empowering our customers with access to responsible credit that can positively transform their lives. Our relentless commitment to innovation and data-driven practices has positioned us as a leader in the industry, and we are actively seeking exceptional individuals to join our team as Senior Software Engineer to play a critical role in driving positive change. Position overview We are seeking a highly skilled Platform Engineer with expertise in building self-serve platforms that combine real-time ML deployment and advanced data engineering capabilities. This role requires a blend of cloud-native platform engineering, data pipeline development, and deployment expertise. The ideal candidate will have a strong background in implementing data workflows, building platforms to enable self-serve for ML pipelines while enabling seamless deployments. Responsibilities Platform Engineering Design and build self-serve platforms that support real-time ML deployment and robust data engineering workflows. Create APIs and backend services using Python and FastAPI to manage and monitor ML workflows and data pipelines. Real-Time ML Deployment Implement platforms for real-time ML inference using tools like AWS SageMaker and Databricks. Enable model versioning, monitoring, and lifecycle management with observability tools such as New Relic. Data Engineering Build and optimise ETL/ELT pipelines for data preprocessing, transformation, and storage using PySpark and Pandas. Develop and manage feature stores to ensure consistent, high-quality data for ML model training and deployment. Design scalable, distributed data pipelines on platforms like AWS, integrating tools such as DynamoDB, PostgreSQL, MongoDB, and MariaDB. CI/CD and Automation Use CI/CD pipelines using Jenkins, GitHub Actions, and other tools for automated deployments and testing. Automate data validation and monitoring processes to ensure high-quality and consistent data workflows. Documentation and Collaboration Create and maintain detailed technical documentation, including high-level and low-level architecture designs. Collaborate with cross-functional teams to gather requirements and deliver solutions that align with business goals. Participate in Agile processes such as sprint planning, daily standups, and retrospectives using tools like Jira. Experience Required Qualifications 5-10 years experience in IT 5-8 years experience in platform backend engineering 1 year experience in DevOps & data engineering roles. Hands-on experience with real-time ML model deployment and data engineering workflows. Technical Skills Strong expertise in Python and experience with Pandas, PySpark, and FastAPI. Proficiency in container orchestration tools such as Kubernetes (K8s) and Docker. Advanced knowledge of AWS services like SageMaker, Lambda, DynamoDB, EC2, and S3. Proven experience building and optimizing distributed data pipelines using Databricks and PySpark. Solid understanding of databases such as MongoDB, DynamoDB, MariaDB, and PostgreSQL. Proficiency with CI/CD tools like Jenkins, GitHub Actions, and related automation frameworks. Hands-on experience with observability tools like New Relic for monitoring and troubleshooting. We are proud to be an Equal Opportunity Employer and consider all qualified applicants for employment opportunities without regard to race, age, color, religion, gender, national origin, disability, sexual orientation, veteran status or any other category protected by the laws or regulations in the locations where we operate. California applicants can find a copy of Oportun's CCPA Notice here: https://oportun.com/privacy/california-privacy-notice/. We will never request personal identifiable information (bank, credit card, etc.) before you are hired. We do not charge you for pre-employment fees such as background checks, training, or equipment. If you think you have been a victim of fraud by someone posing as us, please report your experience to the FBI’s Internet Crime Complaint Center (IC3).

Location: India (Hybrid/Remote Options) About RediMinds We don’t just develop AI—we redefine its boundaries . At RediMinds, we turn theoretical breakthroughs into solutions that revolutionize healthcare, climate resilience, robotics, and human potential. If you’ve ever dreamed of leading research that leaves labs to transform lives, this is your moment. The Role - AI Research Pioneer You’ll lead a nimble, brilliant team of 5–8 researchers to tackle audacious questions: How do we make LLMs diagnose diseases before symptoms appear? Can AI simulate protein folding to cure the incurable? What does ethical superintelligence look like for 8 billion people? This isn’t management—it’s orchestrating a rebellion against the possible . What You’ll Ignite Moonshot Leadership : Direct high-risk/high-reward research in generative AI, neuro-symbolic systems, and causal inference—with resources to match your ambition. Industry-Defining Publications : Publish in Nature , NeurIPS, or ICML while shipping code that runs in hospitals, factories, and farms. Talent Alchemy : Recruit and mentor geniuses (PhDs, rebels, dreamers) into a team that outthinks Google DeepMind. Impact Translation : Partner with RediMinds’ product teams to turn embeddings into empathy, and algorithms into action. Global Thought Leadership : Represent RediMinds at Davos, TED, or the UN—your research will shape policy and humanity’s trajectory. Ideal Profile A PhD in CS, Physics, Neurobiology, Quantum Computing, or any field where you’ve hacked the universe’s rules. 5–6 years leading research at a top-tier lab (OpenAI, DeepMind, MIT, Max Planck) or bleeding-edge tech giant. Published or perished : A track record in venues that make peers gasp (e.g., Science , NeurIPS, CVPR). Engineering grit : Fluency in PyTorch, JAX, HF, CUDA—and battle scars from scaling ideas to petabyte scale. Philosophical depth : You debate AI alignment over chai, and see "ethics" as a technical constraint. Deep experience in one or more of the following domains: LLM training and fine-tuning Knowledge retrieval, vector databases, and RAG pipelines Scientific machine learning (e.g., computational chemistry, physics-informed ML) Vision-Language and Multimodal AI Strong ability to bridge academic theory with real-world AI product development . Excellent communication skills and the ability to inspire, guide, and grow a high-performing research team. Why Choose RediMinds? Build Your Legacy : Lead a team of most ambitious AI researchers from Day 1. Unshackled Resources : No grant applications—just a blank check for compute, talent, and wild creativity. Elite Team: Collaborate with a global network of researchers, product thinkers, and AI engineers across RediMinds’ initiatives. Global Advantage : Shape AI revolution from its epicenter, with proximity to IITs/ISRO and global collaborators. Compensation : Competitive salary in a company valued at tomorrow’s numbers. Relocation support, healthcare for family, and a moonshot budget for conferences, courses, or curiosity. Apply Now If you’re ready to trade incremental papers for planet-scale impact , apply now only if you’re a PhD holder and send us: Your CV (highlight research that bent reality). A 1-page manifesto: “The One Problem I’d Solve with Unlimited Compute.” Links to 2 publications that reveal your intellectual signature. Email to talent@rediminds.com Subject line: “Pioneer Application: [Your Name] - [Your Boldest Idea]” “The universe is not made of atoms—it’s made of courage.” Join us. Rewrite physics.

About Mihira Visual Labs Mihira Visual Labs is a research-driven CGI and VFX studio redefining filmmaking through AI- and ML-powered workflows. We specialize in the development and production of full-length animated films, empowering creators with cutting-edge tools to accelerate high-quality storytelling and IP creation. Our mission is to make world-class storytelling faster, more efficient, and more cost-effective — where human imagination is the only true differentiator. Role Overview The Lead AI/ML Engineer will spearhead the development and integration of artificial intelligence and machine learning solutions into our VFX production pipeline. You’ll work closely with pipeline developers, production managers, and creative teams to reimagine workflows, automate repetitive tasks, and push the boundaries of innovation in photorealistic rendering, stylized animation, and other CGI processes. This role combines deep technical expertise with a strong understanding of the demands of a fast-paced VFX/animation studio. Key Responsibilities AI Strategy & Roadmap Develop and maintain a strategic plan for implementing AI/ML across the VFX pipeline—covering data wrangling, rendering, asset management, animation, and post-production. Identify new approaches to innovate current workflows to increase efficiency and cut down on time. Algorithm & Model Development Research, design, and implement ML models (e.g., computer vision, generative models, style transfer) that improve artist efficiency, production speed, enhance image quality, or enable new creative possibilities. Optimize models for performance on local GPU/CPU clusters or cloud-based infrastructures. Pipeline Integration & Automation Collaborate with pipeline engineers to seamlessly integrate AI agents or tools into existing software stacks (e.g., Maya, Houdini, Nuke), ensuring minimal disruption to artists’ workflows. Develop automated solutions for tasks like rotoscoping, clean-up, crowd simulation, environment generation, or facial capture/animation. Infrastructure & Tooling Architect and maintain robust data pipelines, ensuring the secure collection and organization of high-quality datasets for training AI models. Evaluate and deploy containerization/MLOps tools (Docker, Kubernetes, MLflow, etc.) for scalable model training, inference, and monitoring. Performance Optimization Profile model performance, memory usage, and render times; implement optimizations in frameworks such as TensorFlow, PyTorch, or custom GPU pipelines. Work with DevOps/IT teams to configure and manage dedicated GPU farms or cloud compute resources. Research & Development Stay updated with state-of-the-art ML/DL techniques, particularly in generative AI, computer vision, and real-time rendering. Introduce emerging methods (e.g., stable diffusion, large language models, neural rendering) to innovate new production techniques. Mentorship & Collaboration Lead a small team of AI engineers or data scientists, providing guidance on best practices, code reviews, and architectural decisions. Educate and train production staff on AI-driven tools and workflows, fostering a culture of continuous improvement. Documentation & Reporting Create clear technical documentation for AI solutions, ensuring maintainability and scalability. Present progress, insights, and ROI to executive leadership, project stakeholders, and cross-functional teams. Qualifications & Skills Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field. A PhD is a bonus but not mandatory. 5+ years of professional experience in applied machine learning or data science, with at least 2 years in a lead/managerial role. Previous experience in VFX, animation, gaming, or related entertainment industries is a bonus. Programming: Expert-level Python (C++ is a plus). ML Frameworks: Deep understanding of TensorFlow, PyTorch, scikit-learn, or similar libraries. Computer Vision & Generative Models: Familiarity with CNNs, GANs, autoencoders, stable diffusion, or neural radiance fields. Pipeline Tools: Experience with integration in VFX software (Maya, Houdini, Nuke) and plugin APIs.[Optional] DevOps & MLOps: Comfortable with containerization (Docker), orchestration (Kubernetes), CI/CD, and cloud platforms (AWS, Azure, GCP). Proven track record of translating production challenges into AI/ML solutions that deliver measurable efficiency gains or cost savings. Experience with model optimization (quantization, pruning) and GPU/CPU performance tuning. Collaboration: Excellent communication to bridge technical and creative teams, explaining complex concepts in clear, accessible language. Leadership: Ability to mentor junior engineers and foster a culture of experimentation and continuous learning. Agility: Adapts quickly to evolving project needs, production pipelines, and new AI techniques. A genuine interest in cinema, animation, or gaming—a plus if you have prior knowledge of the Baahubali IP or similar large-scale IPs. Creativity in applying AI to artistic challenges, from photorealistic digital humans to stylized animated sequences.

About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any and all capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset based securitization Spocto - Debt recovery & risk mitigation platform Corpository - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have on-boarded over 17000+ enterprises, 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today, who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come, join the club to be a part of our epic growth story. Responsibilities This particular role is within our Yubi Invest vertical, and you would get to work on building our bonds platform, called Aspero, for retail users. Be able to operate in ambiguous situations and define clear objectives by breaking down the narratives independently. Work closely with business, research, data and engineering teams to understand the user goals, market dynamics and ship products. Aligning product strategy, proposition and roadmap with measurable metrics with all stakeholders. Drive PRDs, product planning, and product design of new features and enhancements. Clearly communicate product and platform benefits to our users and internal stakeholders About The Role- We’re looking for a highly skilled, results-driven AI engineer who thrives in fast-paced, high-impact environments. If you are passionate about pushing the boundaries of Computer Vision, OCR, and Large Language Models (LLMs) and have a strong foundation in building and deploying AI solutions, this role is for you. As a Senior Data Scientist, you will take ownership of designing and implementing state-of-the-art OCR and Computer Vision systems. This role demands deep technical expertise, the ability to work autonomously, and a mindset that embraces complex challenges head-on. Here, you won’t just fine-tune pre-trained models—you’ll be architecting, optimizing, and scaling AI solutions that power real-world applications. Key Responsibilities- Architect, develop, and deploy high-performance Computer Vision and OCR models for real-world applications. Implement and optimize state-of-the-art OCR models such as Donut, TrOCR, LayoutLM, and DocFormer for document processing and information extraction. Fine-tune and integrate LLMs (GPT, LLaMA, Mistral, etc.) to enhance text understanding and automation. Develop custom deep learning models for large-scale image and document processing. Build and optimize end-to-end AI pipelines, ensuring efficient data processing and model deployment. Work closely with engineers to operationalize AI models in production (Docker, FastAPI, TensorRT, ONNX). Enhance GPU performance and model inference efficiency, applying techniques such as quantization and pruning. Stay ahead of industry advancements, continuously experimenting with new AI architectures and training techniques. Work in a highly dynamic, startup-like environment, balancing rapid experimentation with production-grade robustness. Requirements 5-10 years experience p roven technical expertise – Strong programming skills in Python, PyTorch, TensorFlow with deep experience in Computer Vision and OCR. Hands-on experience in developing, training, and deploying OCR and document AI models. Deep understanding of Transformer-based architectures for vision and text processing. Experience working with Hugging Face, OpenCV, TensorRT, and NVIDIA GPUs for model acceleration. Autonomous problem solver – You take initiative, work independently, and drive projects from research to production. Strong experience in scaling AI solutions, including model optimization and deployment on cloud platforms (AWS/GCP/Azure). Thrives in fast-paced environments – You embrace challenges, pivot quickly, and execute effectively. Familiarity with MLOps tools (Docker, FastAPI, Kubernetes) for seamless model deployment. Experience in multi-modal models (Vision + Text). Nice to Have- Strong background in vector databases, RAG pipelines, and fine-tuning LLMs for document intelligence. Contributions to open-source AI projects.

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: More details below: 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. 4+ years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM and LLMs and building blocks Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong development skills in C/C++ 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. 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 Assembly 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.

Position Overview BayOne Solutions is seeking an exceptional AI/ML Engineer to join our innovative technology initiatives that will revolutionize talent acquisition through intelligent automation. This role is critical to developing and implementing cutting-edge AI/ML solutions that will transform core business processes and drive operational excellence. As our AI/ML Engineer, you will architect and deploy sophisticated machine learning models, implement generative AI solutions, and build multimodal AI systems that transform how we connect talent with opportunities. This position offers the opportunity to work with Fortune 500 clients while building scalable AI solutions that will define the future of our technology platform. Key Responsibilities AI/ML Model Development & Implementation (40%) Design and implement advanced machine learning algorithms for candidate-job matching, utilizing semantic understanding and behavioral prediction models Develop natural language processing solutions for job description parsing, candidate profile analysis, and automated content generation Build and optimize recommendation engines that intelligently match candidates to opportunities based on skills, experience, and cultural fit Create predictive models for recruitment outcomes, including candidate success probability and time-to-fill optimization Implement anomaly detection systems for candidate screening and quality assurance Generative AI & Large Language Models (25%) Develop and fine-tune large language models (LLMs) for recruitment-specific applications including automated job description generation, candidate communication, and interview preparation materials Implement RAG (Retrieval-Augmented Generation) systems for intelligent document processing and candidate information extraction Build conversational AI systems for candidate pre-screening, interview scheduling, and engagement campaigns Create prompt engineering solutions and implement advanced generative AI workflows using GPT, LLaMA, and other foundation models Develop multimodal AI applications that process text, voice, and structured data for comprehensive candidate assessment Data Pipeline & Integration (20%) Design and implement robust data pipelines for processing candidate profiles, job descriptions, and recruitment metrics Build ETL processes for integrating multiple data sources including internal systems, critical platforms, and external APIs Develop real-time data processing systems for candidate sourcing and matching operations Implement data quality monitoring and validation systems ensuring high-quality inputs for ML models Create scalable data architectures supporting AI model training, inference, and continuous learning Platform Integration & Deployment (15%) Integrate AI/ML models with the Django-based Recruitment 2.0 platform through RESTfuI APIs and microservices architecture Deploy models to production environments using containerization (Docker) and cloud platforms (Azure/AWS) Implement A/B testing frameworks for model performance evaluation and continuous improvement Build monitoring and alerting systems for model performance, drift detection, and system health Collaborate with full-stack developers to ensure seamless integration of AI capabilities into user- facing applications Required Qualifications Education & Experience Bachelor's degree in Computer Science, Data Science, Machine Learning, or related technical field 2+ years of hands-on experience in machine learning, deep learning, and AI model development Proven track record developing and deploying AI/ML solutions in production environments Experience working with enterprise clients and understanding business requirements for AI applications Technical Skills Programming Languages: Expert-level Python proficiency; experience with C++, SQL, and web technologies ML/AI Frameworks: Advanced experience with TensorFlow, PyTorch, Keras, scikit-learn, and Huggin Face Transformers Generative AI & LLMs: Hands-on experience with GPT models, fine-tuning techniques, prompt engineering, and foundation models NLP & Text Processing: Strong background in natural language processing, text classification, named entity recognition, and semantic analysis Data Processing: Proficiency with NumPy, Pandas, and large-scale data processing frameworks Cloud & DevOps: Experience with Azure/AWS, Docker, Git, and CI/CD pipelines for ML model deployment Databases: Working knowledge of SQL databases, NoSQL systems, and vector databases for AI applications Specialized Experience Experience with multimodal AI systems processing text, audio, and structured data Background in recommendation systems, matching algorithms, and information retrieval Knowledge of automated assessment systems and candidate evaluation methodologies Experience with real-time AI applications and low-latency model serving Understanding of bias detection and fairness in AI systems, particularly for human-oriented applications Preferred Qualifications Master's degree in Machine Learning, AI, or related field Background in developing Al-powered applications for complex business processes Knowledge of federated learning and distributed AI system architectures Experience with document processing, OCR, and information extraction systems Familiarity with enterprise software integration patterns and API development Application Process We are looking for candidates who can start immediately and contribute to our fast-paced, innovative environment. Please submit your resume along with examples of AI/ML projects you've developed, particularly those involving NLP, generative AI, or recommendation systems. Equal Opportunity Employer: Bayone Solutions is committed to creating a diverse and inclusive workplace and is proud to be an equal opportunity employer. This position o[fers an exceptional opportunity to shape the[uture of recruitment technology while working with cutting-edge AI systems and enterprise clients. Join us in building the next generation o[talent solutions.

Software Engineer – AI/ML/LLM/Data Science Company Overview: Entra Solutions (A BSI Financial Services company) is a FinTech company specialized in technology based financial solutions and services for the mortgage Industry. We are a people-focused, growth-oriented, innovative company and we're looking for people like you to make a positive change and join our team today! We are looking for an innovative Software Engineer – AI/ML/LLM/Data Science to design, develop, and deploy AI-driven solutions using Machine Learning, NLP, and Large Language Models (LLMs). The ideal candidate will work with Python to build and optimize retrieval-augmented generation (RAG) systems, LLM fine-tuning, and vector search technologies. You will develop scalable AI pipelines, ensuring high performance and seamless integration with cloud and on-prem environments. This role involves MLOps best practices, AI model optimization, and deployment of intelligent applications. WHAT YOU WILL DO: Develop, fine-tune, and deploy AI/ML models and LLM-based applications for real-world use cases. Build and optimize retrieval-augmented generation (RAG) systems using Vector Databases (e.g., ChromaDB, Pinecone, FAISS). Work on LLM fine-tuning, embeddings, and prompt engineering to enhance model performance. Develop end-to-end AI solutions with APIs using FastAPI, Flask, or similar frameworks. Build and maintain scalable data pipelines for training and inferencing AI models. Deploy and manage models using MLOps best practices on AWS or Azure. Optimize AI model performance for low-latency inference and scalability. Collaborate with cross-functional teams (Product, Engineering, Data Science) to integrate AI capabilities into applications. WHAT WE’RE LOOKING FOR: Must Have: Proficiency in Python – Strong hands-on experience in AI/ML frameworks like TensorFlow, PyTorch, Hugging Face, LangChain, OpenAI APIs. Good to Have: Experience with LLM fine-tuning, embeddings, and transformers. Knowledge of NLP, vector search technologies (ChromaDB, Pinecone, FAISS, Milvus). Experience in building scalable AI models and data pipelines with Spark, Kafka, or Dask. Familiarity with MLOps tools (Docker, Kubernetes, CI/CD for AI models). Hands-on experience in cloud-based AI deployment (AWS Lambda, SageMaker, GCP Vertex AI, Azure ML). Knowledge of prompt engineering, GPT models, or knowledge graphs. WHAT’S IN IT FOR YOU? Competitive Salary & Full Benefits Package PTOs / Medical Insurance Exposure to cutting-edge AI/LLM projects in an innovative environment Career Growth Opportunities in AI/ML leadership Collaborative & AI-driven work culture EEO Statement We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, disability status, protected veteran status or any other characteristic protected by law.

Machine Learning Engineer (L1) Experience Required: 2-4 years As a Machine Learning Engineer at Spring, you’ll help bring data-driven intelligence into our products and operations. You’ll support the development and deployment of models and pipelines that power smarter decisions, more personalized experiences, and scalable automation. This is an opportunity to build hands-on experience in real-world ML and AI systems while collaborating with experienced engineers and data scientists. You’ll work on data processing, model training, and integration tasks — gaining exposure to the entire ML lifecycle, from experimentation to production deployment. You’ll learn how to balance model performance with system requirements, and how to structure your code for reliability, observability, and maintainability. You’ll use modern ML/AI tools such as scikit-learn, HuggingFace, and LLM APIs — and be encouraged to explore AI techniques that improve our workflows or unlock new product value. You’ll also be expected to help build and support automated data pipelines, inference services, and validation tools as part of your contributions. You’ll work closely with engineering, product, and business stakeholders to understand how models drive value. Over time, you’ll build the skills and judgment needed to identify impactful use cases, communicate technical trade-offs, and contribute to the broader evolution of ML at Spring. What You’ll Do Support model development and deployment across structured and unstructured data and AI use cases. Build and maintain automated pipelines for data processing, training, and inference. Use ML and AI tools (e.g., scikit-learn, LLM APIs) in day-to-day development. Collaborate with engineers, data scientists, and product teams to scope and deliver features. Participate in code reviews, testing, and monitoring practices. Integrate ML systems into customer-facing applications and internal tools. Identify differences in data distribution that could affect model performance in real-world applications. Stay up to date with developments in the machine learning industry. Tech Expectations Core Skills Curiosity, attention to detail, strong debugging skills, and eagerness to learn through feedback Solid foundation in statistics and data interpretation Strong understanding of data structures, algorithms, and software development best practices Exposure to data pipelines, model training and evaluation, or training workflows Languages Must Have: Python, SQL ML Algorithms Must Have: Traditional modeling techniques (e.g., tree models, Naive Bayes, logistic regression) Ensemble methods (e.g., XGBoost, Random Forest, CatBoost, LightGBM) ML Libraries / Frameworks Must Have: scikit-learn, Hugging Face, Statsmodels, Optuna Good to Have: SHAP, Pytest Data Processing / Manipulation Must Have: pandas, NumPy Data Visualization Must Have: Plotly, Matplotlib Version Control Must Have: Git Others – Good to Have AWS (e.g., EC2, SageMaker, Lambda) Docker Airflow MLflow Github Actions

Job Family Data Science & Analysis (India) Travel Required Up to 25% Clearance Required None What You Will Do Design, train, and fine-tune advanced foundational models (text, audio, vision) using healthcare-and other relevant datasets, focusing on accuracy and context relevance. Collaborate with cross-functional teams (Business, engineering, IT) to seamlessly integrate AI/ML technologies into our solution offerings. Deploy, monitor, and manage AI models in a production environment, ensuring high availability, scalability, and performance. Continuously research and evaluate the latest advancements in AI/ML and industry trends to drive innovation. Ensure all AI solutions adhere to industry standards and regulatory requirements (i.e., HIPAA). Develop and maintain comprehensive documentation for AI models, including development, training, fine-tuning, and deployment procedures. Provide technical guidance and mentorship to junior AI engineers and team members. Collaborate with stakeholders to understand business needs and translate them into technical requirements for model fine-tuning and development. Select and curate appropriate datasets for fine-tuning foundational models to address specific use cases. Implement robust security protocols to protect sensitive data from breaches and unauthorized access. Ensure AI solutions can seamlessly integrate with existing systems and applications. What You Will Need Bachelors or master’s in computer science, Artificial Intelligence, Machine Learning, or a related field. 10+ year industry experience with minimum of 5 years of hands-on experience in AI/ML, with a demonstrable track record of training and deploying LLMs and other machine learning models. Strong proficiency in Python and familiarity with popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers, etc.). Practical experience deploying and managing AI models in production environments, including expertise in serving and inference frameworks (Triton, TensorRT, VLLM, TGI, etc.). Experience in Voice AI applications, a solid understanding of healthcare data standards (FHIR, HL7, EDI) and regulatory compliance (HIPAA, SOC2) is preferred. Excellent problem-solving and analytical abilities, capable of tackling complex challenges and evaluating multiple factors. Exceptional communication and collaboration skills, enabling effective teamwork in a dynamic environment. Experience with cloud computing platforms (AWS, Azure) and containerization technologies (Docker, Kubernetes) is a plus. Familiarity with MLOps practices for continuous integration, continuous deployment (CI/CD), and automated monitoring of AI models. Delivered a minimum of 3 to 5 AI/LLM medium to large scale projects of significant value. What We Offer What Would Be Nice to Have: Guidehouse offers a comprehensive, total rewards package that includes competitive compensation and a flexible benefits package that reflects our commitment to creating a diverse and supportive workplace. About Guidehouse Guidehouse is an Equal Opportunity Employer–Protected Veterans, Individuals with Disabilities or any other basis protected by law, ordinance, or regulation. Guidehouse will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of applicable law or ordinance including the Fair Chance Ordinance of Los Angeles and San Francisco. If you have visited our website for information about employment opportunities, or to apply for a position, and you require an accommodation, please contact Guidehouse Recruiting at 1-571-633-1711 or via email at RecruitingAccommodation@guidehouse.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodation. All communication regarding recruitment for a Guidehouse position will be sent from Guidehouse email domains including @guidehouse.com or guidehouse@myworkday.com. Correspondence received by an applicant from any other domain should be considered unauthorized and will not be honored by Guidehouse. Note that Guidehouse will never charge a fee or require a money transfer at any stage of the recruitment process and does not collect fees from educational institutions for participation in a recruitment event. Never provide your banking information to a third party purporting to need that information to proceed in the hiring process. If any person or organization demands money related to a job opportunity with Guidehouse, please report the matter to Guidehouse’s Ethics Hotline. If you want to check the validity of correspondence you have received, please contact recruiting@guidehouse.com. Guidehouse is not responsible for losses incurred (monetary or otherwise) from an applicant’s dealings with unauthorized third parties. Guidehouse does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Guidehouse and Guidehouse will not be obligated to pay a placement fee.

Experience : 2.00 + years Salary : INR 1500000-2500000 / year (based on experience) Expected Notice Period : 30 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Office (Pune) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Anervea.AI) (*Note: This is a requirement for one of Uplers' client - Anervea.AI) What do you need for this opportunity? Must have skills required: Airflow, LLMs, NLP, Statistical Modeling, Predictive Analysis, Forecasting, Python, SQL, MLFlow, pandas, Scikit-learn, XgBoost Anervea.AI is Looking for: As an ML / Data Science Engineer at Anervea, you’ll work on designing, training, deploying, and maintaining machine learning models across multiple products. You’ll build models that predict clinical trial outcomes, extract insights from structured and unstructured healthcare data, and support real-time scoring for sales or market access use cases. You’ll collaborate closely with AI engineers, backend developers, and product owners to translate data into product features that are explainable, reliable, and impactful. Key Responsibilities Develop and optimize predictive models using algorithms such as XGBoost, Random Forest, Logistic Regression, and ensemble methods Engineer features from real-world healthcare data (clinical trials, treatment adoption, medical events, digital behavior) Analyze datasets from sources like ClinicalTrials.gov, PubMed, Komodo, Apollo.io, and internal survey pipelines Build end-to-end ML pipelines for inference and batch scoring Collaborate with AI engineers to integrate LLM-generated features with traditional models Ensure explainability and robustness of models using SHAP, LIME, or custom logic Validate models against real-world outcomes and client feedback Prepare clean, structured datasets using SQL and Pandas Communicate insights clearly to product, business, and domain teams Document all processes, assumptions, and model outputs thoroughly Technical Skills Required : Strong programming skills in Python (NumPy, Pandas, scikit-learn, XGBoost, LightGBM) Experience with statistical modeling and classification algorithms Solid understanding of feature engineering, model evaluation, and validation techniques Exposure to real-world healthcare, trial, or patient data (strong bonus) Comfortable working with unstructured data and data cleaning techniques Knowledge of SQL and NoSQL databases Familiarity with ML lifecycle tools (MLflow, Airflow, or similar) Bonus: experience working alongside LLMs or incorporating generative features into ML Bonus: knowledge of NLP preprocessing, embeddings, or vector similarity methods Personal Attributes : Strong analytical and problem-solving mindset Ability to convert abstract questions into measurable models Attention to detail and high standards for model quality Willingness to learn life sciences concepts relevant to each use case Clear communicator who can simplify complexity for product and business teams Independent learner who actively follows new trends in ML and data science Reliable, accountable, and driven by outcomes—not just code Bonus Qualities : Experience building models for healthcare, pharma, or biotech Published work or open-source contributions in data science Strong business intuition on how to turn models into product decisions How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Key Responsibility Lead the fine-tuning and domain adaptation of open-source LLMs (e.g., LLaMA 3) using frameworks like vLLM, HuggingFace, DeepSpeed, and PEFT techniques. Develop data pipelines to ingest, clean, and structure cybersecurity data, including threat intelligence reports, CVEs, exploits, malware analysis, and configuration files. Collaborate with cybersecurity analysts to build taxonomy and structured knowledge representations to embed into LLMs. Drive the design and execution of evaluation frameworks specific to cybersecurity tasks (e.g., classification, summarization, anomaly detection). Own the lifecycle of model development including training, inference optimization, testing, and deployment. Provide technical leadership and mentorship to a team of ML engineers and researchers. Stay current with advances in LLM architectures, cybersecurity datasets, and AI-based threat detection. Advocate for ethical AI use and model robustness, especially given the sensitive nature of cybersecurity data Requirements Required Skills: 5+ years of experience in machine learning, with at least 2 years focused on LLM training or fine-tuning. Strong experience with vLLM, HuggingFace Transformers, LoRA/QLoRA, and distributed training techniques. Proven experience working with cybersecurity data—ideally including MITRE ATT&CK, CVE/NVD databases, YARA rules, Snort/Suricata rules, STIX/TAXII, or malware datasets. Proficiency in Python, ML libraries (PyTorch, Transformers), and MLOps practices. Familiarity with prompt engineering, RAG (Retrieval-Augmented Generation), and vector stores like FAISS or Weaviate. Demonstrated ability to lead projects and collaborate across interdisciplinary teams. Excellent problem-solving skills and strong written & verbal communication. Nice to Have Experience deploying models via vLLM in production environments with FastAPI or similar APIs. Knowledge of cloud-based ML training (AWS/GCP/Azure) and GPU infrastructure. Background in reverse engineering, malware analysis, red teaming, or threat hunting. Publications, open-source contributions, or technical blogs in the intersection of AI and cybersecurity.

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid. Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa. Job Description Visa's Cybersecurity team provides enterprise-wide, risk-based cybersecurity policies, practices, and solutions to protect Visa’s systems and data from internal and external threats. To protect Visa’s assets in this dynamic threat landscape, they are deploying new cyber-security tools, collaborating across industries, and taking a proactive approach to monitoring the cyberspace beyond the Visa network. As part of Cyber Threat Analytics and Research team (CTAR) , you will leverage cutting-edge technologies to perform statistical profiling, inference, classification, clustering and predictive analysis. As a key member of the technical team, you will create and implement sophisticated machine learning models to help derive new insights to defend against cyber-attacks. You will be working with a large variety of data sets, cutting-edge security technologies, and world-class operation teams to create awesome analytics for security and other business units. Essential Functions: Analyze cyber event logs using Spark and big data technologies and develop deeper insights into products using advanced statistical methods. Formulate cyber threat scenarios into technical data problems and develop high fidelity models to capture unseen threats Devise and implement deep learning models for building user behavior profiles. This includes data acquisition, feature engineering, model development, and deployment. Conduct feature engineering on various data sources to build and enrich feature store Fine tune open source LLM to detect anomalous user behavior Leverage Generative AI to perform RAG for helping improve Cyber investigation efficiency As a member of the CTAR team, you will work closely with other data scientists and data engineers to build, design, engineer, and develop analytical software and services that deliver security functionality and improve security efficiency and capabilities through automation. Assist in shaping overall direction, life-cycle management, and leadership for Information Security architecture and technology related to Visa. Communicate clean and persuasive data directly to end users, leadership, and other stakeholders, technical and non-technical. This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs. Qualifications Basic Qualifications: •2+ years of relevant work experience and a Bachelors degree, OR 5+ years of relevant work experience Preferred Qualifications: •3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) •Solid background and hands on experiences with building Machine learning, deep learning and AI models •Experience with Generative AI/LLM •Excellent understanding of algorithms and data structures and proficiency in Python and SQL. •Experience working with large datasets using tools and Hadoop, Spark, or Hive •Excellent analytic and problem-solving capability combined with ambition to solve hard problems •Strong communications skills and ability to collaborate •Highly driven, resourceful and results oriented •Good team player and excellent interpersonal skills •Demonstrated ability to lead and navigate through ambiguity

Job Role: Generative AI Engineer Intern Company: Growhut Technologies Private Limited Job Type: Full-Time Internship Location: Remote Stipend: INR 15,000 - 20,000 per month About Growhut At Growhut, we’re transforming industries with innovative AI solutions. Join our dynamic team to shape the future of technology and redefine possibilities through cutting-edge AI. The Role As a Generative AI Engineer Intern, you will work on groundbreaking AI projects, leveraging state-of-the-art tools and models to solve real-world challenges. What You’ll Do: Learn and experiment with cutting-edge Generative AI models, including GPT-4, PaLM, and Stable Diffusion, to create transformative applications. Assist in developing innovative AI solutions blending language, vision, and audio. Explore transformer architectures and contribute to optimizing them for impactful applications. Gain experience in prompt engineering and few-shot learning to unlock the potential of large language models. Support the team in building scalable inference systems for real-world applications. Collaborate on research initiatives and contribute to new techniques in controllable generation and multi-modal AI systems. Technical Requirements We’re looking for motivated individuals eager to learn and grow in the field of AI. The ideal candidate should have: Basic familiarity with Generative AI models (e.g., GPT-4, Stable Diffusion). Understanding of foundational AI concepts, including transformers and attention mechanisms. Experience with Agentic workflows and working with Conversational AI . Familiarity with LiveKit , AWS (including Lambda functions ), Google Cloud Platform (GCP), and Vertex AI . Interest in prompt engineering and few-shot learning techniques. Familiarity with programming languages like Python and frameworks like PyTorch or TensorFlow. Strong problem-solving skills and a keen interest in AI research. Why Growhut? At Growhut, we offer more than just an internship - we provide an opportunity to shape the future of AI. Here’s what sets us apart: Work on diverse, cutting-edge projects that will challenge and inspire you. Be part of a fast-growing company where your impact is felt immediately. Collaborate with a team of brilliant minds, pushing each other to new heights. The Growhut Difference At Growhut, we believe in AI’s power to change the world. We’re not just riding the wave of the future—we’re creating it. Every day, you’ll be able to work on projects that matter, solving real problems for real people. We’re looking for someone who is eager to learn, excited to take on challenges, and ready to contribute to groundbreaking AI innovations. If you’re ready to kickstart your career in AI, apply now , and let’s reshape the future together!

AI/ML ENGINEER Who We Are? Cleantech Industry Resources accelerates United States solar, battery storage and EV projects by providing turnkey development as a service including 100% internal systems engineering. The company deploys a leading team that spun out of the largest solar power producer in the world. This team operates within a sophisticated suite of software to support projects from land origination, through to commercial operation. Location Chennai What We Offer Opportunity to join a top-notch, collaborative team of professionals Fantastic team environment and collaborative culture Professional development opportunities to grow into an industry leader Medical Insurance for the employee and family Spot Recognition bonus for exceptional performance Long Term Incentive policy Regular team outings, events, and activities to foster a positive work environment Our Commitment to Diversity At CIR, we are dedicated to nurturing a diverse and equitable workforce that truly reflects our community. We deeply value each person’s unique perspective, skills, and experiences. CIR embraces all individuals, regardless of race, religion, sexual orientation, gender identity, age, or nationality. We are steadfast in our commitment to fostering a just and inclusive world through intentional policies and actions. Your individuality enriches our collective strength, and we strive to ensure everyone feels respected, valued, and empowered. Position Summary We are looking for an AI/ML Engineer to build and optimize machine learning models for GIS-based spatial analysis and data-driven decision-making. This role involves working on geospatial AI models, data pipelines, and Retrieval-Augmented Generation (RAG)-based applications for zoning, county sentiment analysis, and regulatory insights. The engineer will also work closely with the data team, leading efforts in data curation and building robust data pipelines to collect, preprocess, and analyse extensive datasets from various geospatial and regulatory sources to generate automated reports and insights. Core Responsibilities Machine Learning for GIS & Spatial Analysis: Develop and deploy ML models for geospatial data processing, forecasting, and automated GIS insights. Work with large-scale geospatial datasets (e.g., satellite imagery, shapefiles, raster/vector data). Create AI models for land classification, feature detection, and geospatial pattern analysis. Optimize spatial data pipelines and build predictive models for environmental and energy sector applications. Retrieval-Augmented Generation (RAG) & NLP Development: Develop RAG-based AI applications to extract insights from zoning, permitting, and regulatory documents. Build LLM-based applications for zoning law interpretation, county sentiment analysis, and compliance predictions. Implement document retrieval and summarization techniques for legal, policy, and energy development reports. Data Engineering & Pipeline Development: Lead the creation of ETL pipelines to collect and preprocess geospatial data for ML model training. Work with PostGIS, PostgreSQL, and cloud storage to manage structured and unstructured data. Collaborate with the data team to design and implement efficient data processing and storage solutions. AI Model Optimization & Deployment: Fine-tune LLMs for domain-specific applications in renewable energy and urban planning. Deploy AI models using cloud-based MLOps frameworks (AWS, GCP, Azure). Optimize ML model inference for real-time GIS applications and geospatial data analysis. Collaboration & Continuous Improvement: Work with cross-functional teams to ensure seamless AI integration with existing business processes. Engage in knowledge sharing and mentoring within the company. Stay updated with latest advancements in AI, GIS, and NLP to improve existing models and solutions. Education Requirements Master’s in Computer Science, Data Science, Machine Learning, Geostatistics, or related fields. Technical Skills and Experience Software Proficiency: Programming: Python (TensorFlow, PyTorch, scikit-learn, pandas, NumPy), SQL. Machine Learning & AI: Deep learning, NLP, retrieval-based AI, geospatial AI, predictive modeling. GIS & Spatial Data Processing: Experience with PostGIS, GDAL, GeoPandas, QGIS, Google Earth Engine. LLM & RAG Development: Experience in fine-tuning LLMs, retrieval models, vector databases (FAISS, Weaviate). Cloud & MLOps: AWS/GCP/Azure, Docker, Kubernetes, MLflow, FastAPI. Big Data Processing: Experience with large-scale data mining, data annotation, and knowledge graph techniques. Database & Storage: PostgreSQL, NoSQL, vector databases, cloud storage solutions. Communication: Strong ability to explain complex AI/ML concepts to non-technical stakeholders. Project Management: Design experience in projects from conception to implementation. Ability to coordinate with other engineers and stakeholders. Renewable Energy Systems: Understanding of solar energy systems and their integration into existing infrastructure Experience 2-4 years of experience Experience in developing AI for energy sector, urban planning, or environmental analysis. Strong understanding of potential prediction, zoning laws, and regulatory compliance AI applications. Familiarity with spatiotemporal ML models and satellite-based geospatial analytics. Psychosocial Skills /Human Skills/Behavioural Skills Strong analytical, organizational, and problem-solving skills. Management experience a plus. Must be a go-getter with an enterprising attitude A self-starter, able to demonstrate high levels of initiative and motivation Entrepreneurial mindset with the ability to take ideas and run with them from concept to conclusion. Technical understanding of clean energy business processes Exceptional verbal and writing communication skills with superiors, peers, partners, and other stakeholders. Excellent interpersonal skills while managing multiple priorities in a fast-paced and ever-changing environment. Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The physical demands of this job require an individual to be able to work at a computer for most of the day, be able to participate in conference calls and travel to team retreats on a time-to-time basis. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Work Conditions The work environment is usually quiet (normal city traffic noises are common), a blend of artificial and natural light, temperate and generally supports a collaborative work environment. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Equal Opportunity Employer At Cleantech Industry Resources, we embrace diversity and uphold a strong dedication to establishing an all-encompassing atmosphere for both our staff and associates. Our choices in employment are free from any bias related to race, creed, nationality, ethnicity, gender, sexual orientation, gender identity, gender expression, age, physical limitations, veteran status, or any other legally safeguarded attributes. Being an integral part of Cleantech Industry Resources means you can expect to be immersed in a realm of professional possibilities within a culture that nurtures teamwork, adaptability, and the embracing of all.

Exp : 15yrs to 23yrs Primary skills :- Vision AI Solution, Nvidia, Computer Vision, Media, Open Stack. Key Responsibilities Define and lead the end-to-end technical architecture for vision-based AI systems across edge and cloud. Design and optimize large-scale video analytics pipelines using NVIDIA DeepStream, TensorRT, and Triton Inference Server. Architect distributed AI systems, including model training, deployment, inferencing, monitoring, and continuous learning. Collaborate with product, research, and engineering teams to translate business requirements into scalable AI solutions. Lead efforts in model optimization (quantization, pruning, distillation) for real-time performance on devices like Jetson Orin/Xavier. Drive the integration of multi-modal AI (vision + language, 3D, audio) where applicable. Guide platform choices (e.g., edge AI vs cloud AI trade-offs), ensuring cost-performance balance. Mentor senior engineers and promote best practices in MLOps, system reliability, and AI observability. Stay current with emerging technologies (e.g., NeRF, Diffusion Models, Vision Transformers, synthetic data). Contribute to internal innovation strategy, including IP generation, publications, and external presentations. ________________________________________ 🛠️ Required Technical Skills Deep expertise in computer vision, deep learning, and multi-modal AI. Proven hands-on experience with: NVIDIA Jetson, DeepStream SDK, TensorRT, Triton Inference Server TAO Toolkit, Isaac SDK, CUDA, cuDNN Strong in PyTorch, TensorFlow, OpenCV, GStreamer, and GPU-accelerated pipelines. Experience deploying vision AI models at large scale (e.g., 1000+ cameras/devices or multi-GPU clusters). Skilled in cloud-native ML infrastructure: Docker, Kubernetes, CI/CD, MLflow, Seldon, Airflow Proficiency in Python, C++, CUDA (or PyCUDA), and scripting. Familiar with 3D vision, synthetic data pipelines, and generative models (e.g., SAM, NeRF, Diffusion). Experience in multi modal (LVM/VLM), SLMs, small LVM/ VLM, Time series Gen AI models, Agentic AI, LLMOps/Edge LLMOps, Guardrails, Security in Gen AI, YOLO/Vision Transformers ________________________________________ 🤝 Soft Skills & Leadership 10+ years in AI/ML/Computer Vision, with 8+ years in technical leadership or architect roles Strong leadership skills with experience mentoring technical teams and driving innovation. Excellent communicator with the ability to engage stakeholders across engineering, product, and business. Strategic thinker with a practical mindset—able to balance innovation with production-readiness. Experience interfacing with enterprise customers, researchers, and hardware partners. ________________________________________ 🧩 Preferred Qualifications MS or PhD in Computer Vision, Machine Learning, Robotics, or a related technical field ( Added Advantage ) Experience with NVIDIA Omniverse, Clara, or MONAI for healthcare or simulation environments. Experience in domains like smart cities, robotics, retail analytics, or medical imaging. Contributions to open-source projects or technical publications. Certifications: NVIDIA Jetson Developer, AWS/GCP AI/ML Certifications.

Primary skill :- NVIDIA Solution Architect, GEN / AI Architect, Azure or AWS cloud. Relevant Exp :- NVIDIA ( 2 to 3 yrs ) Location :- Chennai / Noida. As an NVIDIA Generative AI Solution Architect at , you will lead the design, development, and deployment of AI solutions leveraging NVIDIA’s Edge AI, Computer Vision, Generative AI, and Metropolis technologies . You will collaborate with cross-functional teams and customers to architect scalable, high-performance AI systems integrating real-time computer vision, generative AI workflows, and industrial digital twins on edge, cloud, and metaverse platforms. Key Responsibilities Architect and deliver end-to-end AI solutions using NVIDIA’s AI Enterprise software, NeMo framework, Triton Inference Server, and GPU-accelerated platforms. Design and implement AI pipelines optimized for edge devices (NVIDIA Jetson, Clara), cloud infrastructure (AWS, Azure, GCP), and data centers (NVIDIA DGX). Develop and showcase proof-of-concept solutions using large language models (LLMs), retrieval-augmented generation (RAG), and advanced computer vision models for object detection, segmentation, and video analytics. Utilize NVIDIA Metropolis platform capabilities to architect AI-powered video analytics and smart city solutions, leveraging edge-to-cloud pipelines for real-time insights and automation. Optimize AI inference workloads using CUDA, TensorRT, mixed precision, and model quantization to meet stringent latency and throughput SLAs. Collaborate with company engineering, product, and client teams to embed NVIDIA AI technologies into enterprise workflows and industrial applications. Provide technical leadership, training, and mentorship on NVIDIA SDKs, AI best practices, and solution deployment strategies. Stay abreast of NVIDIA’s product roadmap, AI research trends, and industrial AI innovations to drive continuous solution improvement. Support customer engagements including technical workshops, solution demonstrations, and architectural reviews. Ensure adherence to data privacy, security, and ethical AI standards throughout the solution lifecycle. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related technical field. 5+ years of experience architecting and deploying AI/ML solutions with strong expertise in NVIDIA AI platforms (NeMo, Triton, CUDA, TensorRT). Proven experience with generative AI technologies including large language models, prompt engineering, and RAG workflows. Strong background in computer vision applications, including object detection, segmentation, and video analytics frameworks. Hands-on experience deploying AI solutions on edge devices (NVIDIA Jetson, Clara), cloud platforms (Azure, AWS, GCP), and data center GPU infrastructure. Familiarity with NVIDIA Metropolis platform for AI-powered video analytics and smart infrastructure solutions. Proficiency in Python, C++, and deep learning frameworks such as PyTorch or TensorFlow. Experience with container orchestration (Kubernetes, Docker) and MLOps practices including CI/CD pipelines for AI workloads. Excellent communication skills for engaging technical teams and business stakeholders. Willingness to travel up to 15% for client and NVIDIA events. Preferred Skills Experience optimizing AI inference with TensorRT, mixed precision, and model quantization. Knowledge of AI ethics, bias mitigation, and responsible AI principles. Prior experience in industrial, manufacturing, smart cities, or healthcare domains. Certifications related to NVIDIA AI technologies or cloud platforms (AWS, Azure, GCP). Experience working in global, cross-cultural teams.

Principal Data Scientist Experience : 14-16 years Job Summary We are seeking a highly experienced AI Lead - Principal Data Scientist to spearhead the delivery of multiple AI and machine learning projects across industries such as supply chain, logistics, pricing, manufacturing, and workforce planning. This role combines deep hands-on expertise in AI/ML/Gen AI (50%) with strategic leadership and cross-functional stakeholder management. You will lead enterprise AI solutions from concept to production, architect scalable cloud-native platforms, and collaborate with business and technology teams to deliver measurable business outcomes. Key Responsibilities Technical Leadership & Solutioning : Design, build, and deploy advanced AI, machine learning, deep learning, and Gen AI solutions using Python, Scikit-learn, TensorFlow/PyTorch, and LangChain/OpenAI APIs. Architect and implement end-to-end AI systems including data ingestion, preprocessing, model training, validation, and deployment. Develop modular, reusable components and APIs (FastAPI/Flask) for inference and integration with digital applications. Lead cloud-native development on AWS, Azure, or GCP for scalable deployment of AI models and pipelines. Project & Delivery Ownership Manage the delivery of multiple concurrent AI/ML/Gen AI initiatives, ensuring quality, timeliness, and business alignment. Define technical roadmap, sprint plans, and milestone goals; track delivery KPIs and model performance in production. Guide agile teams through best practices in model lifecycle management, DevOps/MLOps, and reusable IP development. Business Engagement & Techno-Functional Consulting Act as the techno-functional bridge between business and engineering teams to translate high-level problems into AI/ML use cases. Conduct business value assessments, requirement workshops, and stakeholder reviews. Drive adoption by presenting explainable AI results using visual storytelling and decision support tools. Team Enablement & Innovation Mentor and upskill junior data scientists and engineers in best practices, new AI trends, and real-world problem-solving. Stay current with the latest trends in Generative AI, LLMs, Vision AI, and responsible AI practices. Contribute to internal frameworks, accelerators, and reusable artifacts for faster go-to-market. Required Skills & Qualifications Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related quantitative field. 10-13 years of experience in delivering AI/ML solutions at scale with at least 5 years in a lead or principal role. Hands-on expertise in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn) and Generative AI (OpenAI, Llama, LangChain). Strong cloud development experience with AWS, GCP, or Azure, including AI/ML services and containerized deployments. Experience deploying models in production via APIs and integrating with enterprise applications. Excellent communication, stakeholder management, and problem-solving skills. Preferred Qualifications Experience in Generative AI (LLMs, prompt engineering, RAG pipelines). Familiarity with MLOps tools (MLflow, Airflow, DVC, Kubeflow). Working knowledge of data engineering workflows, feature stores, and streaming/batch data pipelines. Exposure to data visualization tools like Streamlit, Dash, or Power BI for presenting insights. Certifications in cloud (AWS/GCP/Azure), AI/ML, or data science. (ref:hirist.tech)

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . 📝 Interview Process: The process consists of 6 stages , including a technical assessment, code review, code discussion , and panel interviews . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.