1535 Mlflow Jobs - Page 39

About the Role: Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore Job Description: We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks : LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture : AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. What’s In It For You? Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our benefits include: Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 316525 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Roles and Responsibilities: Lead the design, development, and implementation of AI/ML-based solutions across various product lines Collaborate with product managers, data engineers, and architects to translate business requirements into data science problems and solutions Take ownership of end-to-end AI/ML modules, from data processing to model development, testing, and deployment Provide technical leadership to a team of data scientists, ensuring high-quality outputs and adherence to best practices Conduct cutting-edge research and capability building across the latest Machine Learning, Deep Learning, and AI technologies Prepare technical documentation, including high-level and low-level design, requirement specifications, and white papers Evaluate and fine-tune models, ensuring they meet performance requirements and deliver insights that drive product improvements Production exposure to Large Language Models (LLM) and experience in implementing and optimizing LLM-based solutions Must-have Skills: 5-10 years of experience in Data Science and AI/ML product development, with a proven track record of leading technical teams Expertise in machine learning algorithms, Deep Learning models, Natural Language Processing, and Anomaly Detection Strong understanding of model lifecycle management, including model building, evaluation, and optimization Hands-on experience with Python and proficiency with frameworks like TensorFlow, Keras, PyTorch, etc Solid understanding of SQL, NoSQL databases, and data modeling with ElasticSearch experience Ability to manage multiple projects simultaneously in a fast-paced, agile environment Excellent problem-solving skills and communication abilities, particularly in documenting and presenting technical concepts Familiarity with Big Data frameworks such as Spark, Storm, Databricks, and Kafka Experience with container technologies like Docker and orchestration tools like Kubernetes, ECS, or EKS Optional (Good To Have) Skills: Experience with cloud-based machine learning platforms like AWS, Azure, or Google Cloud Experience with tools like MLFlow, KubeFlow, or similar for model tracking and orchestration Exposure to NoSQL databases such as MongoDB, Cassandra, Redis, and Cosmos DB, and familiarity with indexing mechanisms Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @ nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status or other characteristics protected by law. Show more Show less

Technical Expertise : (minimum 2 year relevant experience) ● Solid understanding of Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. ● Exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. ● Hands-on experience with modality-specific encoder models (text, image, audio) for multi-modal AI applications. ● Proficient in model fine-tuning, prompt engineering, using both open-source and proprietary LLMs. ● Experience with model quantization, optimization, and conversion techniques (FP32 to INT8, ONNX, TorchScript) for efficient deployment, including edge devices. ● Deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. ● Strong MLOps knowledge with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. ● Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions. ● Familiarity with data preprocessing, standardization, and knowledge graphs (nice to have). ● Strong analytical mindset with a passion for building robust, scalable AI solutions. ● Skilled in Python, writing clean, modular, and efficient code. ● Proficient in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic. ● Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search. ● Exposure to Neo4j and graph databases for relationship-driven insights. ● Hands-on with Docker and containerization to build scalable, reproducible, and portable AI services. ● Up-to-date with the latest in GenAI, LLMs, Agentic AI, and deployment strategies. ● Strong communication and collaboration skills, able to contribute in cross-functional and fast-paced environments. Bonus Skills ● Experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing. ● Working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar Job Type: Full-time Pay: From ₹300,000.00 per year Schedule: Day shift Experience: AI Engineer: 1 year (Required) Work Location: In person Expected Start Date: 23/06/2025

We are looking for a skilled and passionate AI/ML Engineer to join our team and help us build intelligent systems that leverage machine learning and artificial intelligence. You will design, develop, and deploy machine learning models, work closely with cross-functional teams, and contribute to cutting-edge solutions that solve real-world problems. Key Responsibilities: Design and implement machine learning models and algorithms for various use cases (e.g., prediction, classification, NLP, computer vision). Analyze and preprocess large datasets to build robust training pipelines. Conduct research to stay up to date with the latest AI/ML advancements and integrate relevant techniques into projects. Train, fine-tune, and optimize models for performance and scalability. Deploy models to production using tools such as Docker, Kubernetes, or cloud services (AWS, GCP, Azure). Collaborate with software engineers, data scientists, and product teams to integrate AI/ML solutions into applications. Monitor model performance in production and continuously iterate for improvements. Document design choices, code, and models for transparency and reproducibility. Preferred Qualifications: Knowledge in NLP, LLM and GenAI. Knowledge in deep learning architectures such as CNNs, RNNs, transformer models. Experience with NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). Background in deep learning architectures such as CNNs, RNNs, GANs, or transformer models. Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). Contributions to open-source AI/ML projects or publications in relevant conferences/journals. Required 3+ years experience. Work Mode : Onsite. Job Types: Full-time, Permanent Pay: ₹500,000.00 - ₹900,000.00 per year Benefits: Flexible schedule Health insurance Leave encashment Provident Fund Schedule: Day shift Fixed shift Monday to Friday Supplemental Pay: Performance bonus Work Location: In person

Job Description: Join our pioneering team at BuzzBoard, a recognized first-mover in enterprise generative AI, as a Team Lead of Generative AI and LLM. We've already deployed production GenAI systems generating thousands of posts and content pieces monthly across our ecosystem. You'll lead the charge in scaling our mature AI infrastructure while architecting next-generation applications. As a key leader in our Product Team, you'll orchestrate collaboration between Data Engineering, Software Engineering, and AI Operations teams while expanding our proven generative AI innovations. Key Responsibilities: Strategic Leadership & Vision Lead and mentor a team of GenAI engineers and researchers within our mature AI ecosystem Scale our proven production AI systems generating thousands of content pieces monthly across multiple business verticals Define generative AI strategy and roadmap building upon our established first-mover advantage Drive adoption of multimodal AI systems incorporating vision, audio, and text capabilities Contribute and own the GenAI governance frameworks and best practices Advanced AI Development Architect and scale sophisticated generative AI systems building upon our established multi-LLM infrastructure (GPT-4o, Claude Sonnet, Gemini, O1) Optimize our proven tech stack including LangChain, CrewAI, LangGraph, and vector databases (Chroma) Implement advanced RAG, fine-tuning, and prompt engineering across our existing model inventory Lead development of next-generation agentic AI systems with tool use, reasoning capabilities, and autonomous decision-making Enhance our multi-agent orchestration platforms and complex workflow automation Technology Leadership Drive adoption of agentic AI frameworks including LangGraph, CrewAI, AutoGen, and Microsoft Semantic Kernel Lead implementation of multi-agent orchestration platforms and autonomous decision-making systems Oversee vector databases (Pinecone, Weaviate, Chroma) and semantic search systems Lead integration of AI observability and monitoring tools (LangSmith, Weights & Biases, MLflow) Champion AI development platforms and low-code/no-code solutions Enterprise Integration & Scaling Scale our mature AI infrastructure supporting thousands of monthly content generations across multiple business verticals Enhance our proven MLOps and LLMOps practices for continuous model deployment and performance monitoring Drive technical collaboration for seamless AI integration into established production systems Optimize edge AI capabilities and multi-environment deployment strategies Enhance our performance tracking framework including regression testing, edit ratio tracking, and analytics integration Skills and Qualifications: Core Technical Expertise Deep expertise in generative AI systems, large language models, and transformer architectures with proven production experience Expert proficiency in our established tech stack: LangChain, CrewAI, LangGraph, AutoGen, and multi-LLM orchestration Hands-on experience with our model ecosystem: OpenAI GPT, Anthropic, Google, and vector databases Extensive experience with agentic AI frameworks and autonomous workflow orchestration in production environments Hands-on with programming skills in Python with experience in FastAPI, Streamlit, and modern web frameworks Expert-level understanding of prompt engineering, fine-tuning techniques, and model optimization at scale AI Architecture & Operations Experience with vector databases, embedding models, and semantic search implementations Proficiency in containerization (Docker, Kubernetes) and cloud-native AI deployments Knowledge of AI model serving platforms (vLLM, TensorRT-LLM, Ollama) and inference optimization Understanding of AI safety, alignment, and responsible AI development practices Technical Leadership (Individual Contributor Focus) Experience providing technical guidance to engineering teams in fast-paced environments Experience with AI product development lifecycle and technical go-to-market strategies Strong technical communication and ability to explain AI concepts to technical and non-technical audiences Knowledge of AI regulation landscape and compliance requirements Modern AI Ecosystem Familiarity with AI agent frameworks (LangGraph, CrewAI, Microsoft Semantic Kernel) - REQUIRED Experience with compound AI systems and multi-step reasoning architectures - REQUIRED Experience with multimodal AI systems and computer vision integration Understanding of federated learning and privacy-preserving AI techniques Knowledge of AI model evaluation frameworks and benchmarking methodologies Advanced Qualifications: Agentic AI Mastery (Required) Extensive hands-on experience building and deploying agentic AI systems in production environments Deep understanding of tool-calling, function-calling, and API integration within agent workflows Proven track record with multi-agent collaboration patterns and complex reasoning chains Expertise in agent memory systems, context management, and state persistence across interactions Industry Integration Experience scaling production GenAI systems with proven track record of generating thousands of content pieces monthly Knowledge of multi-LLM orchestration and model switching strategies for optimal performance and cost efficiency Understanding of content generation workflows across social media, marketing, and business communications Familiarity with performance monitoring frameworks including regression testing and analytics dashboard integration Research & Innovation Experience with AI model interpretability and explainable AI techniques Knowledge of quantum-classical hybrid AI approaches and emerging paradigms Technical Excellence Advanced degree in Computer Science, AI, or related field (preferred) Experience building and scaling AI teams in fast-paced environments (preferred) Experience with AI ethics committees and responsible AI governance (preferred) Proven ability to drive digital transformation through AI adoption (preferred) Lead the future of GenAI innovation at BuzzBoard, where your expertise will build upon our established success in production generative AI systems. Join a first-mover organization that has already proven the enterprise value of GenAI at scale, generating thousands of content pieces monthly. Your role as Team Lead of Generative AI and LLM will position you to expand our proven AI ecosystem while defining the next generation of agentic AI solutions that drive measurable business impact. Powered by JazzHR 12dkkTUOj7 Show more Show less

Who We Are Zinnia is the leading technology platform for accelerating life and annuities growth. With innovative enterprise solutions and data insights, Zinnia simplifies the experience of buying, selling, and administering insurance products. All of which enables more people to protect their financial futures. Our success is driven by a commitment to three core values: be bold, team up, deliver value – and that we do. Zinnia has over $180 billion in assets under administration, serves 100+ carrier clients, 2500 distributors and partners, and over 2 million policyholders. Who You Are We are looking for a passionate and skilled Python, AI/ML Lead Engineer with 7+ years of experience to join our team. As a Python/AI Lead, you will oversee the development and implementation of machine learning models, AI-driven solutions, and data-driven products. You will guide a team of engineers and collaborate with cross-functional teams to ensure the timely and high-quality delivery of projects. If you thrive in a fast-paced environment and love solving complex problems using data and intelligent algorithms, we’d love to hear from you. What You’ll Do Lead the design, development, and deployment of Gen AI and machine learning solutions using Python. Provide technical guidance and mentorship to team members, ensuring code quality, best practices, and performance optimization. Collaborate with product managers, data scientists, and other stakeholders to define project requirements and objectives. Take ownership of the full software development lifecycle (SDLC), from design to deployment, maintenance, and optimization. Perform code reviews, write technical documentation, and maintain high standards of software quality. Stay up to date with the latest trends and advancements in AI, machine learning, and Python development. Identify and mitigate technical risks in projects while ensuring timely delivery. Foster a collaborative environment and promote knowledge sharing across the engineering team. What You’ll Need 7+ years of professional experience in Python development, with at least 2 years in a technical leadership role. Strong hands-on experience with AI/ML frameworks, Gen AI LLMs and libraries such as TensorFlow, Scikit-learn,or Keras. Python – Strong hands-on experience. Machine Learning – Practical knowledge of supervised, unsupervised, and deep learning techniques. Generative AI – Experience working with LLMs or similar GenAI technologies. API Development – RESTful APIs and integration of ML models into production services. Databases – Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, etc.). Good To Have Skills Cloud Platforms – Familiarity with AWS, Azure, or Google Cloud Platform (GCP). TypeScript/JavaScript – Frontend or full-stack exposure for ML product interfaces. Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, etc.) Exposure to containerization (Docker) and orchestration (Kubernetes). WHAT’S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability Show more Show less

Company Overview Pinnacle Infotech values inclusive growth in an agile, diverse environment. With 30+ years of global experience, 3,400+ experts completed 15,000+ projects across 43+ countries for 5,000+ clients. Join us for rapid advancement, cutting-edge training, and impactful global projects. Embrace E.A.R.T.H. values, celebrate uniqueness, and drive swift career growth with Pinnaclites! Job Title: MLOps Engineer Job Summary: As an MLOps Engineer, you will be responsible for building, deploying, and maintaining the infrastructure required for machine learning models and ETL data pipelines. You will work closely with data scientists, and software developers to streamline our machine learning operations, manage data workflows, and ensure that the ML solutions are scalable, reliable, and secure. Location- Durgapur/Jaipur/Madurai Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of experience in MLOps, data engineering, or a similar role. Proficiency in programming languages such as Python, Spark, and SQL. Experience with ML model deployment frameworks and tools (e.g., MLflow). Hands-on experience with cloud platforms (AWS, Azure, GCP) and infrastructure management. Familiarity with containerization and orchestration tools (Docker, Kubernetes). Understanding of DevOps practices, CI/CD pipelines, and monitoring tools. Excellent problem-solving skills and the ability to work independently and as part of a team. Key Responsibilities: Data Engineering and Pipeline Management: Design, develop, optimize, and maintain ETL processes and data pipelines to collect, process, and store data from multiple sources. Ensure data quality, integrity, and consistency across various databases. Collaborate with data scientists to make data available in the right format and speed for machine learning. Implement and manage data security and privacy protocols as per industry standards. ML Operations and Deployment: Design, build, and optimize scalable and reliable ML deployment pipelines. Develop CI/CD pipelines for automated ML model training, testing, and deployment. Implement and manage containerization (Docker) and orchestration tools (e.g., Kubernetes) for ML workflows. Monitor and troubleshoot model performance and infrastructure, ensuring smooth operation in production environments. Infrastructure Management: Manage cloud infrastructure (AWS, GCP, Azure) to support data and ML operations. Optimize and scale ML and data workflows to handle large-scale datasets. Set up and manage monitoring tools for infrastructure and application performance. Collaboration and Best Practices: Work closely with data science, software development, and product teams to understand project needs and optimize model performance. Develop and document best practices, guidelines, and protocols for ML lifecycle management. Interested candidates, please share your resume at sunitas@pinnacleinfotech.com Show more Show less

Position: AI/ML Engineer (VFX Workflow & Infrastructure) Location: Hyderabad, India Role Overview The 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. 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. What We Offer Impactful Role: Shape the future of VFX and animation filmmaking and leave a lasting mark on flagship studio projects. Career Growth: Lead a growing AI team, collaborate with top-tier VFX artists, and gain exposure to cutting-edge tech. Competitive Compensation: Salary, benefits, and potential for performance-based bonuses. Innovative Environment: Access to advanced hardware, robust R&D budget, and the opportunity to experiment with emerging AI trends. Show more Show less

Position Overview: ShyftLabs is seeking an experienced Databricks Architect to lead the design, development, and optimization of big data solutions using the Databricks Unified Analytics Platform. This role requires deep expertise in Apache Spark, SQL, Python, and cloud platforms (AWS/Azure/GCP). The ideal candidate will collaborate with cross-functional teams to architect scalable, high-performance data platforms and drive data-driven innovation. ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to accelerate business growth across various industries by focusing on creating value through innovation. Job Responsibilities Architect, design, and optimize big data and AI/ML solutions on the Databricks platform. Develop and implement highly scalable ETL pipelines for processing large datasets. Lead the adoption of Apache Spark for distributed data processing and real-time analytics. Define and enforce data governance, security policies, and compliance standards. Optimize data lakehouse architectures for performance, scalability, and cost-efficiency. Collaborate with data scientists, analysts, and engineers to enable AI/ML-driven insights. Oversee and troubleshoot Databricks clusters, jobs, and performance bottlenecks. Automate data workflows using CI/CD pipelines and infrastructure-as-code practices. Ensure data integrity, quality, and reliability across all data processes. Basic Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. 10+ years of hands-on experience in data engineering, with at least 5+ years in Databricks Architect and Apache Spark. Proficiency in SQL, Python, or Scala for data processing and analytics. Extensive experience with cloud platforms (AWS, Azure, or GCP) for data engineering. Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture. Hands-on experience with CI/CD tools and DevOps best practices. Familiarity with data security, compliance, and governance best practices. Strong problem-solving and analytical skills in a fast-paced environment. Preferred Qualifications: Databricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer). Hands-on experience with MLflow, Feature Store, or Databricks SQL. Exposure to Kubernetes, Docker, and Terraform. Experience with streaming data architectures (Kafka, Kinesis, etc.). Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker). Prior experience working with retail, e-commerce, or ad-tech data platforms. We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources. Show more Show less

Role Overview: We are seeking an experienced DevOps Engineer with a strong background in managing AI-related operations and application development processes. The ideal candidate will have a deep understanding of DevOps practices, infrastructure automation, and the deployment and monitoring of AI/ML models in production environments. Key Responsibilities: Set up and maintain CI/CD pipelines (GitHub Actions, GitLab CI/CD, Jenkins) Infra provisioning with Terraform, CloudFormation, or Ansible Manage ML pipelines using Kubeflow, MLflow, Airflow, or Metaflow Deploy and manage containerized services using Docker and Kubernetes (EKS preferred) Design scalable, reliable systems on AWS (Auto Scaling, ELB, ECS/EKS, RDS, S3, CloudFront, etc.) Set up monitoring/logging with Prometheus, Grafana, CloudWatch, ELK, or DataDog Collaborate with data and backend teams for model deployment and lifecycle management Implement security best practices and drive incident response + RCA when needed Stay updated on new DevOps/MLOps tools to improve system efficiency Required Qualifications: 3–5+ years in DevOps or similar role Strong AWS experience — especially with scaling, HA design, and core services (EC2, EKS, RDS, S3) Good experience with CI/CD tools and Infrastructure as Code (Terraform, CloudFormation, Ansible) Hands-on with Docker, Kubernetes, and managing containerized workloads Experience deploying ML models in production environments Familiarity with monitoring and alerting tools (Prometheus, Grafana, ELK, etc.) Cloud and container security awareness Nice to Have: Experience with MLOps platforms (Kubeflow, MLflow, SageMaker, Vertex AI, Metaflow) Scripting in Python or Bash Experience with config management tools like Ansible, Chef, or Puppet Understanding of VPC, IAM, cost optimization, and fault-tolerant architecture About the Company: Griphic is founded by IIT Delhi engineers. Our vision is to enrich lives through technological innovation. We combine cutting-edge AI with hyper-realistic virtual experiences to solve problems and bring disruption in the industry. We have a dynamic team with engineers from IIT Delhi, AI/ML engineers, VR developers, and many more. Our startup is backed by the world’s leading design documentation firm, SKETS Studio, which has a strength of 700+ people and specializes in BIM, architecture, VR, and 3D visualization. Interested candidates should submit their resumes at jobs@griphic.com along with a brief cover letter and any relevant project examples or GitHub links. Show more Show less

Work Experience : 3+ years Salary: 21 LPA Location: Bengaluru Title : MLops Engineer Team Charter: The team in India comes with multi-disciplinary skillset, including but not limited to the following areas: Develop models and algorithms using Deep Learning and Computer Vision on the captured data to provide meaningful analysis to our customers. Some of the projects include – object detection, OCR, barcode scanning, stereovision, SLAM, 3D-reconstruction, action recognition etc. Develop integrated embedded systems for our drones – including embedded system platform development, camera and sensor integration, flight controller and motor control system development, etc. Architect and develop full stack software to interface between our solution and customer database and access – including database development, API development, UI/UX, storage, security and processing for data acquired by the drone. Integration and testing of various off the shelf sensors and other modules with drone and related software. Design algorithms related to autonomy and flight controls. Responsibilities: As a Machine Learning Ops (MLOps) engineer, you will be responsible for building and maintaining the next generation of Vimaan’s ML Platform and Infrastructure. MLOps will have a major contribution in making CV & ML offerings scalable across the company products. We are building all these data & model pipelines to scale Vimaan operations and MLOps Engineer will play a key role in enabling that. You will lead initiatives geared towards making the Computer Vision Engineers at Vimaan more productive. You will setup the infrastructure that powers the ML teams, thus simplifying the development and deployment cycles of ML models. You will help establish best practices for the ML pipeline and partner with other infrastructure ops teams to help champion them across the company. Build and maintain data pipelines - data ingestion, filtering, generating pre-populated annotations, etc. Build and maintain model pipelines - model monitoring, automated triggering of model (re)training, auto-deployment of models to producti on servers and edge devices. Own the cloud stack which comprises all ML resources. Establish standards and practices around MLOps, including governance, compliance, and data security. Collaborate on managing ML infrastructure costs. Qualifications: Deep quantitative/programming background with degree (Bachelors, Masters or Ph.D.) in a highly analytical discipline, like Statistics, Electrical,Electronics, Computer Science, Mathematics, Operations Research, etc. A minimum of 3 years of experience in managing machine learning projects end-to-end focused on MLOps. Experience with building RESTful APIs for monitoring build & production systems using automated monitoring of models and corresponding alarm tools. Experience with data versioning tools such as Data Version Control (DVC). Build and maintain data pipelines by using tools like Dagster, Airflow etc. Experience with containerizing and deploying ML models. Hands-on experience with autoML tools, experiment tracking, model management, version tracking & model training (MLflow, W&B, Neptune etc.), model hyperparameter optimization, model evaluation, and visualization (Tensorboard). Sound knowledge and experience with atleast one DL frameworks such as PyTorch, TensorFlow, Keras. Experience with container technologies (Docker, Kubernetes etc). Experience with cloud services. Working knowledge of SQL based databases. Hands on experience with Python scientific computing stack such as numpy, scipy, scikit-learn Familiarity with Linux and git. Detail oriented design, code debugging and problem-solving skills. Effective communication skills: discussing with peers and driving logic driven conclusions. Ability to perspicuously communicate complex technical/architectural problems and propose solutions for the same. How to stand out Prior experience in deploying ML & DL solutions as services Experience with multiple cloud services. Ability to collaborate effectively across functions in a fast-paced environment. Experience with technical documentation and presentation for effective dissemination of work. Engineering experience in distributed systems and data infrastructure. Show more Show less

Job Description Practice Lead – Generative AI Practitioner Location: Hyderabad Department: AI & Engineering Strategy Experience: 10+ Years Required: - Bachelor’s or master’s degree in computer science, Machine Learning, or a related field; PhD is a plus. - 10+ years of experience in AI/ML, with at least 3 years in Generative AI or foundation model development. - Proven leadership in building GenAI teams or practices at scale. - Hands-on expertise with LLMs (e.g., GPT, LLaMA, Claude), vector databases, LangChain, and orchestration frameworks. - Strong understanding of prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and model evaluation. Preferred: - Experience in building GenAI Centers of Excellence or technical communities of practice. - Familiarity with LLMOps tools (e.g., Weights & Biases, MLflow, TruLens, Guardrails AI). - Certifications in cloud AI/ML platforms (AWS/GCP/Azure). - Recognized thought leadership in GenAI (e.g., speaking engagements, publications, OSS contributions). Show more Show less

Education: Bachelor’s or master’s in computer science, Software Engineering, or a related field (or equivalent practical experience). Hands-On ML/AI Experience: Proven record of deploying, fine-tuning, or integrating large-scale NLP models or other advanced ML solutions. Programming & Frameworks: Strong proficiency in Python (PyTorch or TensorFlow) and familiarity with MLOps tools (e.g., Airflow, MLflow, Docker). Security & Compliance: Understanding of data privacy frameworks, encryption, and secure data handling practices, especially for sensitive internal documents. DevOps Knowledge: Comfortable setting up continuous integration/continuous delivery (CI/CD) pipelines, container orchestration (Kubernetes), and version control (Git). Collaborative Mindset: Experience working cross-functionally with technical and non-technical teams; ability to clearly communicate complex AI concepts. Role Overview Collaborate with cross-functional teams to build AI-driven applications for improved productivity and reporting. Lead integrations with hosted AI solutions (ChatGPT, Claude, Grok) for immediate functionality without transmitting sensitive data while laying the groundwork for a robust in-house AI infrastructure. Develop and maintain on-premises large language model (LLM) solutions (e.g. Llama) to ensure data privacy and secure intellectual property. Key Responsibilities LLM Pipeline Ownership: Set up, fine-tune, and deploy on-prem LLMs; manage data ingestion, cleaning, and maintenance for domain-specific knowledge bases. Data Governance & Security: Assist our IT department to implement role-based access controls, encryption protocols, and best practices to protect sensitive engineering data. Infrastructure & Tooling: Oversee hardware/server configurations (or cloud alternatives) for AI workloads; evaluate resource usage and optimize model performance. Software Development: Build and maintain internal AI-driven applications and services (e.g., automated report generation, advanced analytics, RAG interfaces, as well as custom desktop applications). Integration & Automation: Collaborate with project managers and domain experts to automate routine deliverables (reports, proposals, calculations) and speed up existing workflows. Best Practices & Documentation: Define coding standards, maintain technical documentation, and champion CI/CD and DevOps practices for AI software. Team Support & Training: Provide guidance to data analysts and junior developers on AI tool usage, ensuring alignment with internal policies and limiting model “hallucinations.” Performance Monitoring: Track AI system metrics (speed, accuracy, utilization) and implement updates or retraining as necessary. Job Types: Full-time, Permanent Pay: ₹80,000.00 - ₹90,000.00 per month Benefits: Health insurance Provident Fund Schedule: Day shift Monday to Friday Supplemental Pay: Yearly bonus Work Location: In person Application Deadline: 30/06/2025 Expected Start Date: 30/06/2025

Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Qualifications - External - Undergraduate degree or equivalent experience. •5+ years of experience working with Python, AI •4+ years of experience with SQL Server, MYSQL, Oracle or other comparable RDMS database system •2+ years of experience with APIs / micro-services •2+ years of experience with CI/CD tools like Jenkins, GitHub Actions •1+ years of experience with code scanning and security tools for code vulnerability, code quality, secret scanning, penetration testing and threat modeling Preferred Qualifications: •Bachelor’s degree in computer science or related field •Experience with unit testing frameworks •Experience with version control systems like Git/GitHub •Proven ability to do POC on emerging tech-stack •Experience with Linux or Unix platform •Experience with RabbitMQ •Experience with Redis •Proven ability to independently troubleshoot problems and document RCAs •Experience with event steaming platforms such as Kafka Show more Show less

We’re Hiring: MLOps Engineer (Azure) harshita.panchariya@tecblic.com Location: Ahmedabad, Gujarat Experience: 3–5 Years Employment Type : Full-Time * An immediate joiner will be preferred. Job Summary: We are seeking a skilled and proactive MLOps/DataOps Engineer with strong experience in the Azure ecosystem to join our team. You will be responsible for streamlining and automating machine learning and data pipelines, supporting scalable deployment of AI/ML models, and ensuring robust monitoring, governance, and CI/CD practices across the data and ML lifecycle. Key Responsibilities MLOps : Design and implement CI/CD pipelines for machine learning workflows using Azure DevOps, GitHub Actions, or Jenkins. Automate model training, validation, deployment, and monitoring using tools such as Azure ML, MLflow, or KubeFlow. Manage model versioning, performance tracking, and rollback strategies. Integrate machine learning models with APIs or web services using Azure Functions, Azure Kubernetes Service (AKS), or Azure App Services. DataOps Design, build, and maintain scalable data ingestion, transformation, and orchestration pipelines using Azure Data Factory, Synapse Pipelines, or Apache Airflow. Ensure data quality, lineage, and governance using Azure Purview or other metadata management tools. Monitor and optimize data workflows for performance and cost efficiency. Support batch and real-time data processing using Azure Stream Analytics, Event Hubs, Databricks, or Kafka. DevOps & Infrastructure Provision and manage infrastructure using Infrastructure-as-Code tools such as Terraform, ARM Templates, or Bicep. Set up and manage compute environments (VMs, AKS, AML Compute), storage (Blob, Data Lake Gen2), and networking in Azure. Implement observability using Azure Monitor, Log Analytics, Application Insights, and Skills : Strong hands-on experience with Azure Machine Learning, Azure Data Factory, Azure DevOps, and Azure Storage solutions. Proficiency in Python, Bash, and scripting for automation. Experience with Docker, Kubernetes, and containerized deployments in Azure. Good understanding of CI/CD principles, testing strategies, and ML lifecycle management. Familiarity with monitoring, logging, and alerting in cloud environments. Knowledge of data modeling, data warehousing, and SQL. Preferred Qualifications Azure Certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate, or Azure DevOps Engineer Expert). Experience with Databricks, Delta Lake, or Apache Spark on Azure. Exposure to security best practices in ML and data environments (e.g., identity management, network security). Soft Skills Strong problem-solving and communication skills. Ability to work independently and collaboratively with data scientists, ML engineers, and platform teams. Passion for automation, optimization, and driving operational excellence. harshita.panchariya@tecblic.com Show more Show less

As a AI/ML Engineer, you will be responsible for designing, developing, and implementing machine learning algorithms and AI solutions that address complex business challenges. You will lead a team of engineers collaborating with cross-functional teams to drive the successful deployment of AI initiatives. Your expertise will be crucial in shaping our AI strategy and ensuring the delivery of high-quality, scalable solutions. Key Responsibilities: Lead the design and development of machine learning models and AI solutions to solve business problems. Select appropriate machine learning or deep learning models based on problem context and data availability. Develop, train, test, and validate models using state-of-the-art methodologies and frameworks. Collaborate with analytics, developers and domain experts to acquire, clean, and preprocess large datasets. Engineer features and performs exploratory data analysis to ensure data quality and model readiness. Containerize models (Docker/Kubernetes), implement monitoring (Prometheus/Grafana), and automate pipelines (MLflow/Kubeflow). Implement models into production environments, ensuring robustness, scalability, and maintainability. Develop and maintain CI/CD pipelines for seamless model integration and deployment. Monitor and evaluate model performance post-deployment and iterate based on feedback and performance metrics. Document model architecture, development processes, and performance evaluations thoroughly. Share insights and technical know-how with team members to foster a culture of continuous learning and improvement. Research & Innovation: Stay ahead of AI trends (LLMs, generative AI) and advocate for ethical AI practices. Analyze large datasets to extract insights and improve model performance. Ensure compliance with data privacy and security regulations in all AI/ML initiatives. Qualifications: Bachelor's or master's degree in computer science, Data Science, Machine Learning, or a related field. Proven experience (3+ years) in AI/ML engineering, with a strong portfolio of successful projects. Proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)

Your Day-to-Day Provide technical leadership and guidance to teams of software engineers, fostering a culture of collaboration, innovation, and continuous improvement. Establish outcomes and key results (OKRs) and successfully deliver them. Drive improvements in key performance indicators (KPIs). Increase the productivity and velocity of delivery teams. Develop, plan, and execute engineering roadmaps that bring value and quality to our customers. Collaborate and coordinate across teams and functions to ensure technical, product, and business objectives are met. Instill end-to-end ownership of products, projects, features, modules, and services that you and your team deliver in all phases of the software development lifecycle. What do you need to bring 10+ years of experience in the software industry, with 3+ years of professional experience leading software development teams. Strong critical thinking and problem-solving skills with the ability to address complex technical and non-technical challenges. Experience building and developing engineering teams that exhibit strong ownership, user empathy, and engineering excellence. Proven track record of delivering high-quality systems and software in Big Data Technologies including Spark, Airflow, Hive, etc., with practical exposure to integrating machine learning workflows into data pipelines. Proven track record of delivering high-quality systems and software in Java/J2EE technologies and distributed systems, with experience deploying ML models into production at scale using REST APIs, streaming platforms, or batch inference. Excellent communication skills with the ability to collaborate effectively with cross-functional teams (including data scientists and ML engineers) and manage stakeholders expectations. Ability to coach and mentor talent to reach their full potential, including guiding teams in adopting MLOps best practices and understanding AI model lifecycle management. Experience in building large scale, high throughput, low latency systems, including real-time data processing systems that support personalization, anomaly detection, or predictive analytics. Strong understanding of software development methodologies, modern technology topics and frameworks, and developer operations best practices. Experience with ML platforms (e.g., Kubeflow, MLflow) and familiarity with model monitoring, feature engineering, and data versioning tools is a plus. Provide leadership to others, particularly junior engineers who work on the same team or related product features. Proven experience delivering complex software projects and solutions effectively through Agile methodologies on a regular release cadence. Strong verbal and written communication skills. Strong customer focus, ownership, urgency and drive.

Who are we Fulcrum Digital is an agile and next-generation digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries, including banking & financial services, insurance, retail, higher education, food, healthcare, and manufacturing. Job Summary: We are seeking a skilled and innovative Azure AI Engineer to design, build, and deploy intelligent applications and solutions using Microsoft Azure AI services. The ideal candidate will have a strong background in machine learning, natural language processing, and cloud-native architectures, with a focus on leveraging Azure’s AI and Machine Learning capabilities to solve real-world problems. Key Responsibilities: Design and develop AI solutions using Azure Cognitive Services, Azure Machine Learning, Azure OpenAI, and other Azure-based tools. Implement and deploy machine learning models, NLP models, and computer vision solutions in a scalable and secure Azure environment. Collaborate with data scientists, software developers, and DevOps teams to integrate AI services into applications and business workflows. Monitor, evaluate, and improve model performance using tools like Azure ML, MLflow, and responsible AI dashboards. Ensure solutions comply with data privacy, ethical AI, and security standards. Automate and optimize ML pipelines using Azure ML Pipelines and DevOps integration. Stay updated on new Azure AI features and best practices, and recommend improvements. Requirements Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. 3+ years of hands-on experience with Microsoft Azure, especially in AI/ML services. Proficiency in Python, Azure SDKs, and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with Azure Machine Learning Studio, Data Factory, Blob Storage, and Azure Functions. Familiarity with REST APIs, containers (Docker), and CI/CD pipelines. Strong understanding of data preprocessing, feature engineering, model deployment, and monitoring. Preferred Qualifications: Azure AI Engineer Associate or Microsoft Certified: Azure Solutions Architect certification. Experience with Azure OpenAI, ChatGPT, or large language models. Exposure to Responsible AI principles and tools. Knowledge of MLOps, model versioning, and A/B testing in production environments. Benefits Work with stakeholders to identify automation opportunities and tailor solutions to business needs. Perform data preprocessing, feature engineering, and model training to create high-performing solutions. Experience with data analysis tools and techniques to uncover insights and optimize models. Microsoft Azure AI certification will be Big Plus Job Opening ID RRF_5394 Job Type Permanent Industry IT Services Date Opened 12/06/2025 City Pune City Province Maharashtra Country India Postal Code 411057

Job title: AI/ML Data Scientist Location: Hyderabad About The Job Transform healthcare through innovation. At Sanofi, we're not just developing treatments—we're pioneering the future of healthcare by harnessing the power of data insights and responsible AI to accelerate breakthrough therapies. As an AI/ML Scientist on our AI and Computational Sciences team, you'll: Drive innovation that directly impacts patient outcomes Collaborate with world-class scientists to solve complex healthcare challenges Apply advanced AI techniques to increase drug development success rates Shape the responsible use of AI in life-saving medical research Be part of a mission that matters. Help us transform data into life-changing treatments and join a team where your expertise can make a meaningful difference in patients' lives. Our Team The AI and Computational Sciences team is a key team within R&D Digital, focused on image, omics, wearable sensor data, and clinical data analytics. This team plays a critical role in bridging the gap between general purposed digital products and specific project needs. We are looking for a skilled AI/ML Data Scientist to join our elite AI and Computational Sciences team and harness cutting-edge AI to revolutionize healthcare. As a key player within R&D Digital, you'll transform complex data into life-changing medical breakthroughs. Impact You'll Make Drive Innovation Across Multiple High-impact Domains Precision Medicine: Develop patient response prediction models that personalize treatments Advanced Omics Analysis: Pioneer cell type and cell stage quantification techniques Advanced Image/Video Analysis: Lead application of state-of-art computer vision methods for gaining unprecedented insights about drug efficacy from medical images/videos Digital Health: Design novel biomarkers from wearable sensor data Biological Insights: Create enzyme property prediction algorithms and conduct disease pathway analyses Your Growth Journey Technical Mastery: Develop expertise across image analysis, time series modeling, GenAI, AI Agents, and explainable AI Scientific Impact: Publish in top-tier AI/ML journals and secure patents that protect groundbreaking innovations Global Influence: Deploy solutions that impact patients worldwide Your Environment Elite Team: Work alongside AI/ML experts and drug development experts in an agile, high-performance environment Cutting-Edge Resources: Access Sanofi's state-of-the-art cloud infrastructure and data platforms Continuous Learning: Receive mentorship and training opportunities to sharpen your leadership and AI/ML skills Join Our AI-First Vision Be part of Sanofi's bold transformation into an AI-first organization where you'll: Develop your skills through world-class mentorship and training Chase the miracles of science to improve people's lives Ready to transform healthcare through the power of AI? Main Responsibilities Research Phase Excellence Design and implement AI models for target identification and validation using multi-omics data (genomics, proteomics, transcriptomics) Develop predictive algorithms to molecular design for compound selection and accelerate lead optimization Create computer vision systems for high-throughput screening image analysis and cellular phenotyping Clinical Development Innovation Engineer digital biomarkers from wearable sensors and mobile devices to enable objective, continuous patient monitoring Implement advanced time-series analysis of real-time patient data to detect early efficacy signals Design AI-powered patient stratification models to identify responder populations and optimize trial design Multi-Modal Data Integration Architect systems that harmonize diverse data types (imaging, omics, clinical, text, sensor) into unified analytical frameworks Develop novel feature extraction techniques across modalities to enhance predictive power Create visualization tools that present complex multi-modal insights to clinical teams Scientific Impact Collaborate with cross-functional teams to translate AI insights into actionable drug development strategies Present findings to scientific and business stakeholders with varying technical backgrounds Publish innovative methodologies in top-tier scientific and AI/ML journals Contribute to patent applications to protect novel AI/ML approaches About You Experience : 3 to 5 years of experience in AI/ML and computational model development on multimodal data like omics, biomedical imaging, text and clinical trials data Key Functional Requirement Demonstrated track record of successful AI/ML project implementation 3-5 years of experience in computational modeling or AI/ML algorithm development, or any other related field Deep understanding and proven track record of developing model training pipelines and workflows Excellent communication and collaboration skills Working knowledge and comfort working with Agile methodologies Technical Skills Programming Proficiency: Advanced Python skills with experience in ML frameworks (PyTorch, TensorFlow, JAX) Machine Learning: Deep expertise in supervised, unsupervised, and reinforcement learning algorithms Drug discovery: molecular design, docking, binding site prediction, mRNA vaccine design, ADMET property, protein structure prediction, molecular dynamics simulation Deep Learning: Experience designing and implementing neural network architectures (CNNs, RNNs, Transformers) Computer Vision: Proficiency in image processing, segmentation, and object detection techniques (SAM, ViT, Diffusion Models, MediaPipe, MMPose, MonoDepth, VoxelNet, SlowFast, C3D) Natural Language Processing: Experience with large language models, text mining, and information extraction (OpenAI, Claude, Llama, Qwen, Deepseek model series) Time Series Analysis: Expertise in analyzing temporal data from sensors and wearable devices (HAR foundation models, compliance detection models) Omics Analysis: Knowledge of computational methods for protein genomics, proteomics, or transcriptomics data Cloud Computing: Experience deploying ML models on cloud platforms (AWS) Tools And Technologies Data Processing: Experience with data pipelines and ETL processes Version Control: Proficiency with Git and collaborative development workflows, Docker MLOps: Experience with model deployment, monitoring, and maintenance Visualization: Ability to create compelling data visualizations (Matplotlib, Seaborn, Plotly) Experiment Tracking: Familiarity with tools like MLflow, Weights & Biases, or similar platforms Soft Skills Strong scientific communication abilities for technical and non-technical audiences Collaborative mindset for cross-functional team environments Problem-solving approach with ability to translate business needs into technical solutions Self-motivated with capacity to work independently and drive projects forward Education : PhD/MS/BE/BTech/ME/MTech in Computer Science and Engineering, AI/ML, other relevant engineering discipline, Computational Biology, Data Science, Bioinformatics or related fields (with equivalent experience) Preferred : Publications or public github Languages : English Why Choose us? Bring the miracles of science to life alongside a supportive, future-focused team Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs Opportunity to work in an international environment, collaborating with diverse business teams and vendors, working in a dynamic team, and fully empowered to propose and implement innovative ideas. Pursue Progress . Discover Extraordinary . Progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. You can be one of those people. Chasing change, embracing new ideas and exploring all the opportunities we have to offer. Let’s pursue progress. And let’s discover extraordinary together. At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com! null Show more Show less

Experience : 5.00 + years Salary : INR 1500000-2000000 / year (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Hybrid (Ahmedabad) Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Inferenz) What do you need for this opportunity? Must have skills required: ML model deployment, MLOps, Monitoring Inferenz is Looking for: Job Description: Position: Sr. MLOps Engineer Location: Ahmedabad, Pune Required Experience: 5+ Years of experience Preferred: Immediate Joiners Job Overview: Building the machine learning production infrastructure (or MLOps) is the biggest challenge most large companies currently have in making the transition to becoming an AI-driven organization. We are looking for a highly skilled MLOps Engineer to join our team. As an MLOps Engineer, you will be responsible for designing, implementing, and maintaining the infrastructure that supports the deployment, monitoring, and scaling of machine learning models in production. You will work closely with data scientists, software engineers, and DevOps teams to ensure seamless integration of machine learning models into our production systems. The job is NOT for you if: You don’t want to build a career in AI/ML. Becoming an expert in this technology and staying current will require significant self-motivation. You like the comfort and predictability of working on the same problem or code base for years. The tools, best practices, architectures, and problems are all going through rapid change — you will be expected to learn new skills quickly and adapt. Key Responsibilities: Model Deployment: Design and implement scalable, reliable, and secure pipelines for deploying machine learning models to production. Infrastructure Management: Develop and maintain infrastructure as code (IaC) for managing cloud resources, compute environments, and data storage. Monitoring and Optimization: Implement monitoring tools to track the performance of models in production, identify issues, and optimize performance. Collaboration: Work closely with data scientists to understand model requirements and ensure models are production ready. Automation: Automate the end-to-end process of training, testing, deploying, and monitoring models. Continuous Integration/Continuous Deployment (CI/CD): Develop and maintain CI/CD pipelines for machine learning projects. Version Control: Implement model versioning to manage different iterations of machine learning models. Security and Governance: Ensure that the deployed models and data pipelines are secure and comply with industry regulations. Documentation: Create and maintain detailed documentation of all processes, tools, and infrastructure. Qualifications: 5+ years of experience in a similar role (DevOps, DataOps, MLOps, etc.) Bachelor’s or master’s degree in computer science, Engineering, or a related field. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) Strong understanding of machine learning lifecycle, data pipelines, and model serving. Proficiency in programming languages such as Python, Shell scripting, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.). Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.) Experience with CI/CD tools like Jenkins, GitLab CI, or similar Experience building end-to-end systems as a Platform Engineer, ML DevOps Engineer, or Data Engineer (or equivalent) Strong software engineering skills in complex, multi-language systems Comfort with Linux administration Experience working with cloud computing and database systems Experience building custom integrations between cloud-based systems using APIs Experience developing and maintaining ML systems built with open-source tools Experience developing with containers and Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (MLFlow, KubeFlow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology and best practices Understanding of regulatory requirements for data privacy and model governance. Preferred Skills: Excellent problem-solving skills and ability to troubleshoot complex production issues. Strong communication skills and ability to collaborate with cross-functional teams. Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack). Knowledge of database systems (SQL, NoSQL). Experience with Generative AI frameworks Preferred cloud-based or MLOps/DevOps certification (AWS, GCP, or Azure) 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! Show more Show less

About The Role Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore Job Description We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect, ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks: LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture: AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. What’s In It For You? Our Purpose Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our Benefits Include Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring And Opportunity At S&P Global At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 316525 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India Show more Show less

About The Role Grade Level (for internal use): 12 Lead Agentic AI Developer Location: Gurgaon, Hyderabad and Bangalore Job Description A Lead Agentic AI Developer will drive the design, development, and deployment of autonomous AI systems that enable intelligent, self-directed decision-making. Their day-to-day operations focus on advancing AI capabilities, leading teams, and ensuring ethical, scalable implementations. Responsibilities AI System Design and Development: Architect and build autonomous AI systems that integrate with enterprise workflows, cloud platforms, and LLM frameworks. Develop APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Team Leadership and Mentorship: Lead cross-functional teams of AI engineers, data scientists, and developers. Mentor junior staff in agentic AI principles, reinforcement learning, and ethical AI governance. Customization and Advancement: Optimize autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Fine-tune LLMs, multi-agent frameworks, and feedback loops to align with business goals. Ethical AI Governance: Monitor AI behavior, audit decision-making processes, and implement safeguards to ensure transparency, fairness, and compliance with regulatory standards. Innovation and Research: Spearhead R&D initiatives to advance agentic AI capabilities. Experiment with emerging frameworks (e.g.,Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems. Documentation and Thought Leadership: Publish technical white papers, case studies, and best practices for autonomous AI. Share insights at conferences and contribute to open-source AI communities. System Validation: Oversee rigorous testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation. Validate alignment with ethical and performance benchmarks. Stakeholder Leadership: Collaborate with executives, product teams, and compliance officers to align AI initiatives with strategic objectives. Advocate for AI-driven innovation across the organization. Required Skills/Qualifications What We’re Looking For : Technical Expertise: 8+ years as a Senior AI Engineer, ML Architect, or AI Solutions Lead, with 5+ years focused on autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js. Hands-on experience with autonomous AI tools: LangChain, Autogen, CrewAI, or custom agentic frameworks. Proficiency in cloud platforms: AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI. Experience with MLOps pipelines (e.g., Kubeflow, MLflow) and scalable deployment of AI agents. Leadership: Proven track record of leading AI/ML teams, managing complex projects, and mentoring technical staff. Ethical AI: Familiarity with AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and bias mitigation techniques. Communication: Exceptional ability to translate technical AI concepts for non-technical stakeholders. Nice To Have Contributions to AI research (published papers, patents) or open-source AI projects (e.g., TensorFlow Agents, AutoGen). Experience with DevOps/MLOps tools: Kubeflow, MLflow, Docker, or Terraform. Expertise in NLP, computer vision, or graph-based AI systems. Familiarity with quantum computing or neuromorphic architectures for AI. What’s In It For You? Our Purpose Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress. Our People We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all. From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference. Our Values Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global. Our Benefits Include Health & Wellness: Health care coverage designed for the mind and body. Flexible Downtime: Generous time off helps keep you energized for your time on. Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference. For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries Global Hiring And Opportunity At S&P Global At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning) Job ID: 316524 Posted On: 2025-06-11 Location: Gurgaon, Haryana, India Show more Show less

AI / Generative AI Engineer Location: Remote ( Pan India ) Job Type: Fulltime NOTE: "Only immediate joiners or candidates with a notice period of 15 days or less will be considered" Overview: We are seeking a highly skilled and motivated AI/Generative AI Engineer to join our innovative team. The ideal candidate will have a strong background in designing, developing, and deploying artificial intelligence and machine learning models, with a specific focus on cutting-edge Generative AI technologies. This role requires hands-on experience with one or more major cloud platforms (Google Cloud Platform - GCP, Amazon Web Services - AWS) and/or modern data platforms (Databricks, Snowflake) . You will be instrumental in building and scaling AI solutions that drive business value and transform user experiences. Key Responsibilities: Design and Development: Design, build, train, and deploy scalable and robust AI/ML models, including traditional machine learning algorithms and advanced Generative AI models (e.g., Large Language Models - LLMs, diffusion models). Develop and implement algorithms for tasks such as natural language processing (NLP) , text generation, image synthesis, speech recognition, and forecasting. Work extensively with LLMs, including fine-tuning, prompt engineering, retrieval-augmented generation (RAG) , and evaluating their performance. Develop and manage data pipelines for data ingestion, preprocessing, feature engineering, and model training, ensuring data quality and integrity. Platform Expertise: Leverage cloud AI/ML services on GCP (e.g., Vertex AI, AutoML, BigQuery ML, Model Garden, Gemini) , AWS (e.g., SageMaker, Bedrock, S3 ), Databricks, and/or Snowflake to build and deploy solutions. Architect and implement AI solutions ensuring scalability, reliability, security, and cost-effectiveness on the chosen platform(s). Optimize data storage, processing, and model serving components within the cloud or data platform ecosystem. MLOps and Productionization: Implement MLOps best practices for model versioning, continuous integration/continuous deployment (CI/CD), monitoring, and lifecycle management. Deploy models into production environments and ensure their performance, scalability, and reliability. Monitor and optimize the performance of AI models in production, addressing issues related to accuracy, speed, and resource utilization. Collaboration and Innovation: Collaborate closely with data scientists, software engineers, product managers, and business stakeholders to understand requirements, define solutions, and integrate AI capabilities into applications and workflows. Stay current with the latest advancements in AI, Generative AI, machine learning, and relevant cloud/data platform technologies. Lead and participate in the ideation and prototyping of new AI applications and systems. Ensure AI solutions adhere to ethical standards, responsible AI principles, and regulatory requirements, addressing issues like data privacy, bias, and fairness. Documentation and Communication: Create and maintain comprehensive technical documentation for AI models, systems, and processes. Effectively communicate complex AI concepts and results to both technical and non-technical audiences. Required Qualifications: 8+ years of experience with software development in one or more programming languages, and with data structures/algorithms/Data Architecture. 3+ years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). 3+ years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Proven experience as an AI Engineer, Machine Learning Engineer, or a similar role. Strong programming skills in Python. Familiarity with other languages like Java, Scala, or R is a plus. Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning concepts (e.g., CNNs, RNNs, Transformer s), and statistical modeling. Hands-on experience with developing and deploying Generative AI models and techniques, including working with Large Language Models ( LLMs like GPT, BERT, LLaMA, etc .). Proficiency in using common A I/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Keras, Hugging Face Transformers, LangChain, etc. Demonstrable experience with at least one of the following cloud/data platforms: GCP: Experience with Vertex AI, BigQuery ML, Google Cloud Storage, and other GCP AI/ML services . AWS: Experience with SageMaker, Bedrock, S3, and other AWS AI/ML services . Databricks: Experience building and scaling AI/ML solutions on the Databricks Lakehouse Platform , including MLflow. Snowflake: Experience leveraging Snowflake for data warehousing, data engineering for AI/ML workloads , and Snowpark. Experience with data engineering, including data acquisition, cleaning, transformation, and building ETL/ELT pipelines. Knowledge of MLOps tools and practices for model deployment, monitoring, and management. Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Show more Show less

Overview Data Science Team works in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Pipelines. You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models. You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Active contributor to code & development in projects and services Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption. Partner with ML engineers working on industrialization. Communicate with business stakeholders in the process of service design, training and knowledge transfer. Support large-scale experimentation and build data-driven models. Refine requirements into modelling problems. Influence product teams through data-based recommendations. Research in state-of-the-art methodologies. Create documentation for learnings and knowledge transfer. Create reusable packages or libraries. Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Leverage big data technologies to help process data and build scaled data pipelines (batch to real time) Implement end-to-end ML lifecycle with Azure Databricks and Azure Pipelines Automate ML models deployments Qualifications BE/B.Tech in Computer Science, Maths, technical fields. Overall 2-4 years of experience working as a Data Scientist. 2+ years’ experience building solutions in the commercial or in the supply chain space. 2+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus. Fluent in SQL syntaxis. 2+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. 2+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Pyspark development. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models. Knowledge of Time series/Demand Forecast models is a plus Programming Skills - Hands-on experience in statistical programming languages like Python, Pyspark and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Cloud (Azure) - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool. Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities Experience with Agile methodology for team work and analytics ‘product’ creation. Experience in Reinforcement Learning is a plus. Experience in Simulation and Optimization problems in any space is a plus. Experience with Bayesian methods is a plus. Experience with Causal inference is a plus. Experience with NLP is a plus. Experience with Responsible AI is a plus. Experience with distributed machine learning is a plus Experience in DevOps, hands-on experience with one or more cloud service providers AWS, GCP, Azure(preferred) Model deployment experience is a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is preferred Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Stakeholder engagement-BU, Vendors. Experience building statistical models in the Retail or Supply chain space is a plus Show more Show less

Job Description Key Responsibilities: Model Development: Design, develop, and fine-tune Machine Learning Models Generative AI: Implement Generative AI use cases using frameworks like LangChain, AutoGen, CrewAI etc Research: Conduct research to advance the state-of-the-art in generative AI, including exploring new algorithms, techniques, and tools Collaboration: Work along with Seniors and Stake holders to capture the requirements and execute it in Agile methodology Documentation: Maintain comprehensive documentation of models, experiments, and findings to facilitate knowledge sharing and reproducibility Stay Updated: Keep abreast of the latest developments in the field of AI and machine learning and apply this knowledge to current projects Qualifications Must Have: Proficiency in Python Programming Language Experience in Developing Machine Learning models using Sklearn/PyTorch/TensorFlow Experience with Natural Language Processing (NLP) libraries and tools such as Spark NLP, Hugging Face, NLTK etc Experience in any GenAI framework such as LangChain, AutoGen or CrewAI etc Experience in Github and CI/CD pipelines to deploy the Machine Learning Models Good to Have: Experience in MLOps Tools like MLflow, AutoML etc Experience in Azure Cloud Experience in working Agile Model Additional Information Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) About NIQ NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook Our commitment to Diversity, Equity, and Inclusion NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion Show more Show less