1480 Mlflow Jobs - Page 36

Job Summary: We are looking for a highly capable and automation-driven MLOps Engineer with 2+ years of experience in building and managing end-to-end ML infrastructure. This role focuses on operationalizing ML pipelines using tools like DVC, MLflow, Kubeflow, and Airflow, while ensuring efficient deployment, versioning, and monitoring of machine learning and Generative AI models across GPU-based cloud infrastructure (AWS/GCP). The ideal candidate will also have experience in multi-modal orchestration, model drift detection, and CI/CD for ML systems. Key Responsibilities: Develop, automate, and maintain scalable ML pipelines using tools such as Kubeflow, MLflow, Airflow, and DVC. Set up and manage CI/CD pipelines tailored to ML workflows, ensuring reliable model training, testing, and deployment. Containerize ML services using Docker and orchestrate them using Kubernetes in both development and production environments. Manage GPU infrastructure and cloud-based deployments (AWS, GCP) for high-performance training and inference. Integrate Hugging Face models and multi-modal AI systems into robust deployment frameworks. Monitor deployed models for drift, performance degradation, and inference bottlenecks, enabling continuous feedback and retraining. Ensure proper model versioning, lineage, and reproducibility for audit and compliance. Collaborate with data scientists, ML engineers, and DevOps teams to build reliable and efficient MLOps systems. Support Generative AI model deployment with scalable architecture and automation-first practices. Qualifications: 2+ years of experience in MLOps, DevOps for ML, or Machine Learning Engineering. Hands-on experience with MLflow, DVC, Kubeflow, Airflow, and CI/CD tools for ML. Proficiency in containerization and orchestration using Docker and Kubernetes. Experience with GPU infrastructure, including setup, scaling, and cost optimization on AWS or GCP. Familiarity with model monitoring, drift detection, and production-grade deployment pipelines. Good understanding of model lifecycle management, reproducibility, and compliance. Preferred Qualifications : Experience deploying Generative AI or multi-modal models in production. Knowledge of Hugging Face Transformers, model quantization, and resource-efficient inference. Familiarity with MLOps frameworks and observability stacks. Experience with security, governance, and compliance in ML environments. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Job description Job Title: Tech Lead (AI/ML) – Machine Learning & Generative AI Location: Nagpur (Hybrid / On-site) Experience: 8–15 years Employment Type: Full-time Job Summary: We are seeking a highly experienced Python Developer with a strong background in traditional Machine Learning and growing proficiency in Generative AI to join our AI Engineering team. This role is ideal for professionals who have delivered scalable ML solutions and are now expanding into LLM-based architectures, prompt engineering, and GenAI productization. You’ll be working at the forefront of applied AI, driving both model performance and business impact across diverse use cases. Key Responsibilities: Design and develop ML-powered solutions for use cases in classification, regression, recommendation, and NLP. Build and operationalize GenAI solutions, including fine-tuning, prompt design, and RAG implementations using models such as GPT, LLaMA, Claude, or Gemini. Develop and maintain FastAPI-based services that expose AI models through secure, scalable APIs. Lead data modeling, transformation, and end-to-end ML pipelines, from feature engineering to deployment. Integrate with relational (MySQL) and vector databases (e.g., ChromaDB, FAISS, Weaviate) to support semantic search, embedding stores, and LLM contexts. Mentor junior team members and review code, models, and system designs for robustness and maintainability. Collaborate with product, data science, and infrastructure teams to translate business needs into AI capabilities. Optimize model and API performance, ensuring high availability, security, and scalability in production environments. Core Skills & Experience: Strong Python programming skills with 5+ years of applied ML/AI experience. Demonstrated experience building and deploying models using TensorFlow, PyTorch, scikit-learn, or similar libraries. Practical knowledge of LLMs and GenAI frameworks, including Hugging Face, OpenAI, or custom transformer stacks. Proficient in REST API design using FastAPI and securing APIs in production environments. Deep understanding of MySQL (query performance, schema design, transactions). Hands-on with vector databases and embeddings for search, retrieval, and recommendation systems. Strong foundation in software engineering practices: version control (Git), testing, CI/CD. Preferred/Bonus Experience: Deployment of AI solutions on cloud platforms (AWS, GCP, Azure). Familiarity with MLOps tools (MLflow, Airflow, DVC, SageMaker, Vertex AI). Experience with Docker, Kubernetes, and container orchestration. Understanding of prompt engineering, tokenization, LangChain, or multi-agent orchestration frameworks. Exposure to enterprise-grade AI applications in BFSI, healthcare, or regulated industries is a plus. What We Offer: Opportunity to work on a cutting-edge AI stack integrating both classical ML and advanced GenAI. High autonomy and influence in architecting real-world AI solutions. A dynamic and collaborative environment focused on continuous learning and innovation. Show more Show less

Key Responsibilities: Design and develop a modular, scalable AI platform to serve foundation model and RAG-based applications. Build pipelines for embedding generation , document chunking , and indexing . Develop integrations with vector databases like Pinecone , Weaviate , Chroma , or FAISS . Orchestrate LLM flows using tools like LangChain , LlamaIndex , and OpenAI APIs . Implement RAG architectures to combine generative models with structured and unstructured knowledge sources. Create robust APIs and developer tools for easy adoption of AI models across teams. Build observability and monitoring into AI workflows for performance, cost, and output quality. Collaborate with DevOps, Data Engineering, and Product to align platform capabilities with business use cases. Core Skill Set: Strong experience in Python, with deep familiarity in ML/AI frameworks (PyTorch, Hugging Face, TensorFlow). Experience building LLM applications , particularly using LangChain , LlamaIndex , and OpenAI or Anthropic APIs . Practical understanding of vector search , semantic retrieval , and embedding models . Familiarity with AI platform tools (e.g., MLflow, Kubernetes, Airflow, Prefect, Ray Serve). Hands-on with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes). Solid grasp of RAG architecture design , prompt engineering , and model evaluation . Understanding of MLOps, CI/CD, and data pipelines in production environments. Preferred Qualifications: Experience designing and scaling internal ML/AI platforms or LLMOps tools. Experience with fine-tuning LLMs or customizing embeddings for domain-specific applications. Contributions to open-source AI platform components. Knowledge of data privacy, governance, and responsible AI practices. What You’ll Get: A high-impact role building the core AI infrastructure of our company. Flexible work environment and competitive compensation. Access to cutting-edge foundation models and tooling. Opportunity to shape the future of applied AI within a fast-moving team. Show more Show less

Company Description Technocratic Solutions is a trusted and renowned provider of technical resources on a contract basis, serving businesses globally. With a dedicated team of developers, we deliver top-notch software solutions in cutting-edge technologies such as PHP, Java, JavaScript, Drupal, QA, Blockchain AI, and more. Our mission is to empower businesses worldwide by offering high-quality technical resources that meet project requirements and objectives. We prioritize exceptional customer service and satisfaction, delivering our services quickly, efficiently, and cost-effectively. Join us and experience the difference of working with a reliable partner driven by excellence and focused on your success. Job Title: AI/ML Engineer – Generative AI, Databricks, R Programming Location: Delhi NCR / Pune Experience Level: 5 years Job Summary: We are seeking a highly skilled and motivated AI/ML Engineer with hands-on experience in Generative AI, Databricks, and R programming to join our advanced analytics team. The ideal candidate will be responsible for designing, building, and deploying intelligent solutions that drive innovation, automation, and insight generation using modern AI/ML technologies. --- Key Responsibilities: Develop and deploy scalable ML and Generative AI models using Databricks (Spark-based architecture). Build pipelines for data ingestion, transformation, and model training/inference on Databricks. Implement and fine-tune Generative AI models (e.g., LLMs, diffusion models) for various use cases like content generation, summarization, and simulation. Leverage R for advanced statistical modeling, data visualization, and integration with ML pipelines. Collaborate with data scientists, data engineers, and product teams to translate business needs into technical solutions. Ensure reproducibility, performance, and governance of AI/ML models. Stay updated with the latest trends and technologies in AI/ML and GenAI and apply them where applicable. --- Required Skills & Qualifications: Bachelor's/Master’s degree in Computer Science, Data Science, Statistics, or a related field. 5 years of hands-on experience in Machine Learning/AI, with at least 2 year in Generative AI. Proficiency in Databricks, including Spark MLlib, Delta Lake, and MLflow. Strong command of R programming, especially for statistical modeling and data visualization (ggplot2, dplyr, caret, etc.). Experience with LLMs, transformers (HuggingFace, LangChain, etc.), and other GenAI frameworks. Familiarity with Python, SQL, and cloud platforms (AWS/Azure/GCP) is a plus. Excellent problem-solving, communication, and collaboration skills. Preferred: Certifications in Databricks, ML/AI (e.g., Azure/AWS ML), or R. Experience in regulated industries (finance, healthcare, etc.). Exposure to MLOps, CI/CD for ML, and version control (Git). --- What We Offer: Competitive salary and benefits Flexible work environment Opportunities for growth and learning in cutting-edge AI/ML Collaborative and innovative team culture --- Would you like this tailored to a specific company, industry, or seniority level (e.g., Lead, Junior, Consultant)? Show more Show less

Senior AI/ML Engineer Experience: 5+ years Mode of Engagement: Full-time / Part-time No of Positions: 2 Educational Qualification: B.E./B.Tech/M.E./M.Tech in Computer Science, AI/ML, or related field Industry: IT – AI/ML Services Notice Period: Immediate or 15 days preferred What We Are Looking For: Experience in Chatbot agents, agents which can read data and detect issues/risk/modify data as per input and document data extraction - accurately extract required data from pdf even input pdf is inconsistent Strong experience (5+ years) in backend development using Python (preferred), Java, or Node.js. 2+ years of hands-on experience building LLM-powered applications and LLM agents. Expertise in AI/ML system architecture including Model Context Protocol (MCP) and agent-based reasoning. Proven track record with Docker, Kubernetes, and cloud-based deployment of ML models. Strong collaboration, communication, and problem-solving abilities. Responsibilities: Design, develop, and deploy LLM-based applications and intelligent agent systems. Architect MCP systems to orchestrate interactions between LLMs, APIs, and databases. Containerize AI/ML models and manage deployments using Docker and Kubernetes. Develop and maintain scalable backend systems and data integration. Collaborate with cross-functional teams on technical specifications and product goals. Stay up to date with advancements in LLMs, planning frameworks, and agent tools. Troubleshoot AI models or deployment issues and ensure high availability of systems. Mentor junior engineers and contribute to team-wide knowledge-sharing. Qualifications: Bachelor’s or master's in computer science or relevant technical discipline. 5+ years in backend software development; 2+ years in LLM technologies. Experience with agent-based frameworks like LangChain, LlamaIndex, or AutoGen. Solid foundation in container orchestration and CI/CD using Docker & Kubernetes. Familiarity with MLOps tools like MLflow, Kubeflow, or Seldon Core is a plus. Cloud experience (AWS/GCP/Azure) preferred; Git proficiency required. Added advantages: publications, open-source contributions, or fine-tuning LLMs. Show more Show less

Full Stack AI Developer – LLM & Workflow Automation 📍 Remote | 🕒 8–10 Years | 🧠 Python, React, LLMs, n8n 🧩 About the Role: We’re hiring a Full Stack AI Developer to build next-gen applications that combine intelligent chatbots, LLM workflows, and seamless UI/UX interfaces. You’ll own features end-to-end, from backend APIs and AI integrations to frontend web experiences. 🎯 Key Responsibilities: Design, develop, and deploy full-stack AI-powered applications Build responsive web interfaces using React (or Angular/Vue) Integrate LLMs (OpenAI, Claude, etc.) for smart assistants, summarization, etc. Create and orchestrate automation flows with n8n Build and maintain APIs using Python (FastAPI/Django) Deploy solutions in cloud-native environments (AWS, Azure) Work with cross-functional teams on feature delivery, testing, and scaling ✅ Must-Have Skills: 8–10 years of full-stack development experience Strong in Python for backend and AI integrations (FastAPI, Django) Proficient in React.js (or Angular/Vue) for building modern UIs Hands-on experience with n8n automation workflows Experience integrating LLMs (OpenAI, LangChain, GPT, Claude) REST APIs, webhooks, and third-party integrations Cloud platforms (AWS, Azure, or GCP) CI/CD pipelines, Docker, and SQL/NoSQL databases 🌟 Nice to Have: Experience with MLOps (MLflow, SageMaker, Kubeflow) Familiarity with RAG pipelines, vector DBs (FAISS, Pinecone) Semantic Kernel or multi-agent LLM frameworks Azure certifications This is a remote offshore position, with exciting long-term projects and the chance to work with a dynamic, global tech team. To apply: Send your resume to info@ribbitzllc.com Show more Show less

Key Responsibilities: Design, develop, and deploy AI models and algorithms to solve business problems. Work with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Train, test, and validate models using large datasets. Integrate AI solutions into existing products and applications. Collaborate with data scientists, software engineers, and product teams to build scalable AI solutions. Monitor model performance and continuously improve accuracy and efficiency. Stay updated with the latest AI trends, tools, and best practices. Ensure AI models are ethical, unbiased, and secure. Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 4 to 5 Years of Proven experience in developing and deploying AI/ML solutions. Proficiency in Python and libraries like NumPy, Pandas, OpenCV, etc. Solid understanding of machine learning, deep learning, and NLP techniques. Experience with cloud platforms (AWS, Azure, or Google Cloud) is a plus. Strong problem-solving skills and ability to translate business needs into technical solutions. Excellent communication and collaboration skills. Preferred Qualifications: Experience with data preprocessing, feature engineering, and model tuning. Familiarity with reinforcement learning or generative AI models. Knowledge of MLOps tools and pipelines (e.g., MLflow, Kubeflow). Hands-on experience in deploying AI applications to production environments. Job Types: Full-time, Permanent Pay: ₹1,200,000.00 - ₹2,000,000.00 per year Benefits: Flexible schedule Paid sick time Paid time off Provident Fund Location Type: In-person Schedule: Day shift Fixed shift Monday to Friday Ability to commute/relocate: Gandhinagar, Gujarat: Reliably commute or planning to relocate before starting work (Required) Experience: Android Development: 3 years (Required) Work Location: In person

Designation: Senior Analyst – Data Science Level: L2 Experience: 4 to 6 years Location: Chennai Job Description: We are seeking an experienced MLOps Engineer with 4-6 years of experience to join our dynamic team. In this role, you will build and maintain robust machine learning infrastructure that enables our data science team to deploy and scale models for credit risk assessment, fraud detection, and revenue forecasting. The ideal candidate has extensive experience with MLOps tools, production deployment, and scaling ML systems in financial services environments. Responsibilities: Design, build, and maintain scalable ML infrastructure for deploying credit risk models, fraud detection systems, and revenue forecasting models to production Implement and manage ML pipelines using Metaflow for model development, training, validation, and deployment Develop CI/CD pipelines for machine learning models ensuring reliable and automated deployment processes Monitor model performance in production and implement automated retraining and rollback mechanisms Collaborate with data scientists to productionize models and optimize them for performance and scalability Implement model versioning, experiment tracking, and metadata management systems Build monitoring and alerting systems for model drift, data quality, and system performance Manage containerization and orchestration of ML workloads using Docker and Kubernetes Optimize model serving infrastructure for low-latency predictions and high throughput Ensure compliance with financial regulations and implement proper model governance frameworks Skills: 4-6 years of professional experience in MLOps, DevOps, or ML engineering, preferably in fintech or financial services Strong expertise in deploying and scaling machine learning models in production environments Extensive experience with Metaflow for ML pipeline orchestration and workflow management Advanced proficiency with Git and version control systems, including branching strategies and collaborative workflows Experience with containerization technologies (Docker) and orchestration platforms (Kubernetes) Strong programming skills in Python with experience in ML libraries (pandas, numpy, scikit-learn) Experience with CI/CD tools and practices for ML workflows Knowledge of distributed computing and cloud-based ML infrastructure Understanding of model monitoring, A/B testing, and feature store management. Additional Skillsets: Experience with Hex or similar data analytics platforms Knowledge of credit risk modeling, fraud detection, or revenue forecasting systems Experience with real-time model serving and streaming data processing Familiarity with MLFlow, Kubeflow, or other ML lifecycle management tools Understanding of financial regulations and model governance requirements Job Snapshot Updated Date 13-06-2025 Job ID J_3745 Location Chennai, Tamil Nadu, India Experience 4 - 6 Years Employee Type Permanent

Role : Data Scientist Experience : 1 to 4 Years Work Mode : WFO / Hybrid /Remote if applicable Immediate Joiners Preferred Required Skills & Qualification : An ideal candidate will have experience, as we are building an AI-powered workforce intelligence platform that helps businesses optimize talent strategies, enhance decision making, and drive operational efficiency. Our software leverages cutting-edge AI, NLP, and data science to extract meaningful insights from vast amounts of structured and unstructured workforce data. As part of our new AI team, you will have the opportunity to work on real-world AI applications, contribute to innovative NLP solutions, and gain hands on experience in building AI-driven products from the ground up. Required Skills & Qualification Strong experience in Python programming 1-3 years of experience in Data Science/NLP (Freshers with strong NLP projects are welcome). Proficiency in Python, PyTorch, Scikit-learn, and NLP libraries (NLTK, SpaCy, Hugging Face). Basic knowledge of cloud platforms (AWS, GCP, or Azure). Experience with SQL for data manipulation and analysis. Assist in designing, training, and optimizing ML/NLP models using PyTorch, NLTK, Scikit- learn, and Transformer models (BERT, GPT, etc.). Familiarity with MLOps tools like Airflow, MLflow, or similar. Experience with Big Data processing (Spark, Pandas, or Dask). Help deploy AI/ML solutions on AWS, GCP, or Azure. Collaborate with engineers to integrate AI models into production systems. Expertise in using SQL and Python to clean, preprocess, and analyze large datasets. Learn & Innovate Stay updated with the latest advancements in NLP, AI, and ML frameworks. Strong analytical and problem-solving skills. Willingness to learn, experiment, and take ownership in a fast-paced startup environment. Nice To Have Requirements For The Candidate Desire to grow within the company Team player and Quicker learner Performance-driven Strong networking and outreach skills Exploring aptitude & killer attitude Ability to communicate and collaborate with the team at ease. Drive to get the results and not let anything get in your way. Critical and analytical thinking skills, with a keen attention to detail. Demonstrate ownership and strive for excellence in everything you do. Demonstrate a high level of curiosity and keep abreast of the latest technologies & tools Ability to pick up new software easily and represent yourself peers and co-ordinate during meetings with Customers. What We Offer We offer a market-leading salary along with a comprehensive benefits package to support your well-being. Enjoy a hybrid or remote work setup that prioritizes work-life balance and personal well being. We invest in your career through continuous learning and internal growth opportunities. Be part of a dynamic, inclusive, and vibrant workplace where your contributions are recognized and rewarded. We believe in straightforward policies, open communication, and a supportive work environment where everyone thrives. (ref:hirist.tech) Show more Show less

Job Title Data Scientist (AI for Computer Vision) Job Description We are seeking an experienced Data Scientist specializing in AI for Computer Vision to join our dynamic team. Your primary responsibilities will include developing, fine-tuning, and optimizing AI models for computer vision applications, driving innovation in various healthcare applications. You will work closely with cross-functional teams, including machine learning engineers, software developers, and product managers, to deliver state-of-the-art AI solutions. Your role: Explore and develop innovative Artificial Intelligence (AI) algorithms for healthcare applications Create and refine AI algorithms for pre- and post-processing of images and videos, focusing on data from various imaging modalities Develop and implement machine learning and deep learning techniques for segmentation, classification, and statistical modeling. Demonstrate expertise in image processing, object detection, segmentation, and classification. Proficient in Python programming Possess a strong understanding of algorithms and frameworks such as TensorFlow, PyTorch, and Keras Experienced with version control systems (e.g., Git) and software development practices Develop and Optimize Computer Vision Models: Design, train, and fine-tune DL models for real-world applications Data Preparation & Engineering: Gather, clean, and preprocess large-scale image and video datasets for training and evaluation of computer vision models Experimentation & Model Evaluation: Conduct A/B testing and assess model performance using quantitative metrics (e.g., IoU, mAP, precision, recall) Research & Innovation: Stay updated with the latest advancements in computer vision, deep learning, and related technologies Deployment & Scaling: Work with ML engineers to deploy models into production environments using cloud platforms (AWS, Azure) and frameworks like TensorFlow, PyTorch, and OpenCV Collaboration & Communication: Work closely with cross-functional teams to integrate computer vision solutions into business processes and applications. You're the right fit if: Bachelor’s or master’s Degree: In computer science, AI, Data Science, Machine Learning, or a related field Experience: 3+ years in machine learning, deep learning, or AI research, with at least 1 year of hands-on experience in developing computer vision-based AI applications Programming Proficiency: Strong proficiency in Python and ML frameworks like TensorFlow and PyTorch Domain Knowledge: Knowledge of computer vision, natural language processing (NLP), or multimodal AI applications Technical Skills: Familiarity with computer vision techniques and fine-tuning of models Problem-Solving Skills: Strong problem-solving skills and the ability to work in a fast-paced, research-driven environment MLOps Tools: Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes) Ethical AI: Understanding of ethical AI and bias mitigation in computer vision models. Publications and Contributions: Strong publication record or contributions to open-source AI projects. How We Work Together We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. this role is an office role. About Philips We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others. Learn more about our business. Discover our rich and exciting history. Learn more about our purpose. If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here. Show more Show less

Role Overview As a Test Automation Lead at Dailoqa, you’ll architect and implement robust testing frameworks for both software and AI/ML systems. You’ll bridge the gap between traditional QA and AI-specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance. Key Responsibilities Test Automation Strategy & Framework Design Design and implement scalable test automation frameworks for frontend (UI/UX) , backend APIs , and AI/ML model-serving endpoints using tools like Selenium, Playwright, Postman, or custom Python/Java solutions. Build GenAI-specific test suites for validating prompt outputs, LLM-based chat interfaces, RAG systems, and vector search accuracy. Develop performance testing strategies for AI pipelines (e.g., model inference latency, resource utilization). Continuous Testing & CI/CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions, Jenkins, or GitLab CI/CD. Implement shift-left testing by embedding automated checks into development workflows (e.g., unit tests, contract testing). AI/ML Model Validation Collaborate with data scientists to test AI/ML models for accuracy , fairness , stability , and bias mitigation using tools like TensorFlow Model Analysis or MLflow. Validate model drift and retraining pipelines to ensure consistent performance in production. Quality Metrics & Reporting Define and track KPIs. Test coverage (code, data, scenarios) Defect leakage rate Automation ROI (time saved vs. maintenance effort) Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews. Drive adoption of AI-specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation). Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development. Ability to communicate technical risks to non-technical stakeholders. Collaborative mindset to work with cross-functional teams (data scientists, ML engineers, DevOps). Requirements Technical Requirements Must-Have 5–8 years in test automation, with 2+ years validating AI/ML systems. Expertise in: Automation tools: Selenium, Playwright, Cypress, REST Assured, Locust/JMeter CI/CD: Jenkins, GitHub Actions, GitLab AI/ML testing: Model validation, drift detection, GenAI output evaluation Languages: Python, Java, or JavaScript Certifications: ISTQB Advanced, CAST, or equivalent. Experience with MLOps tools: MLflow, Kubeflow, TFX Familiarity with vector databases (Pinecone, Milvus) and RAG workflows. Strong programming/scripting experience in JavaScript, Python, Java, or similar Experience with API testing, UI testing, and automated pipelines Understanding of AI/ML model testing, output evaluation, and non-deterministic behavior validation Experience with testing AI chatbots, LLM responses, prompt engineering outcomes, or AI fairness/bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile/Scrum methodology and tools like Azure Boards Show more Show less

About the Open Position Join us as Cloud Engineer at Dailoqa , where you will be responsible for operationalizing cutting-edge machine learning and generative AI solutions, ensuring scalable, secure, and efficient deployment across infrastructure. You will work closely with data scientists, ML engineers, and business stakeholders to build and maintain robust MLOps pipelines, enabling rapid experimentation and reliable production implementation of AI models, including LLMs and real-time analytics systems. To be successful as Cloud Engineer you should have experience with: Cloud sourcing, networks, VMs, performance, scaling, availability, storage, security, access management Deep expertise in one or more cloud platforms: AWS, Azure, GCP Strong experience in containerization and orchestration (Docker, Kubernetes, Helm) Familiarity with CI/CD tools: GitHub Actions, Jenkins, Azure DevOps, ArgoCD, etc. Proficiency in scripting languages (Python, Bash, PowerShell) Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML Strong understanding of DevOps principles applied to ML workflows. Key Responsibilities may include: · Design and implement scalable, cost-optimized, and secure infrastructure for AI-driven platforms. · Implement infrastructure as code using tools like Terraform, ARM, or Cloud Formation. · Automate infrastructure provisioning, CI/CD pipelines, and model deployment workflows. · Ensure version control, repeatability, and compliance across all infrastructure components. · Set up monitoring, logging, and alerting frameworks using tools like Prometheus, Grafana, ELK, or Azure Monitor. · Optimize performance and resource utilization of AI workloads including GPU-based training/inference Experience with Snowflake, Databricks for collaborative ML development and scalable data processing. Understanding model interpretability, responsible AI, and governance. Contributions to open-source MLOps tools or communities. Strong leadership, communication, and cross-functional collaboration skills. Knowledge of data privacy, model governance, and regulatory compliance in AI systems. Exposure to LangChain, Vector DBs (e. g. , FAISS, Pinecone), and retrieval-augmented generation (RAG) pipelines. Show more Show less

About Us: Waltcorp is at the forefront of cloud engineering, helping businesses transform their operations by leveraging the power of Google Cloud Platform (GCP) . We are seeking a skilled and visionary GCP DevOps Solutions Architect – ML/AI Focus to design and implement cloud solutions that address our clients' complex business challenges. Key Responsibilities: Solution Design: Collaborate with stakeholders to understand business requirements and design scalable, secure, and high-performing GCP cloud architectures . Technical Leadership: Serve as a technical advisor, guiding teams on GCP best practices, services, and tools to optimize performance, security, and cost efficiency. Infrastructure Development: Architect and oversee the deployment of cloud solutions using GCP services such as Compute Engine, Cloud Storage, Cloud Functions, Cloud SQL , and more. Infrastructure as Code (IaC) & Cloud Automation: Design, implement, and manage infrastructure using Terraform, Google Cloud Deployment Manager , or Pulumi . Automate provisioning of compute, storage, and networking resources using GCP services like Compute Engine, Cloud Storage, VPC, IAM, GKE (Google Kubernetes Engine), Cloud Run . Implement and maintain CI/CD pipelines (using Cloud Build, Jenkins, GitHub Actions , or GitLab CI ). ML Model Deployment & Automation (MLOps): Build and optimize end-to-end ML pipelines using Vertex AI Pipelines, Kubeflow , or MLflow . Automate training, testing, validation, and deployment of ML models in staging and production environments. Support model versioning, reproducibility, and lineage tracking using tools like DVC, Vertex AI Model Registry , or MLflow . Monitoring & Logging: Implement monitoring for both infrastructure and ML workflows using Cloud Monitoring, Prometheus, Grafana, Vertex AI Model Monitoring . Set up alerting for anomalies in ML model performance (data drift, concept drift). Ensure application logs, model outputs, and system metrics are centralized and accessible. Containerization & Orchestration: Containerize ML workloads using Docker and orchestrate using GKE or Cloud Run . Optimize resource usage through autoscaling and right-sizing of ML workloads in containers. Data & Experiment Management: Integrate with data versioning tools (e.g., DVC or LakeFS ) to track datasets used in model training. Enable experiment tracking using MLflow, Weights & Biases , or Vertex AI Experiments . Support reproducible research and automated experimentation pipelines. Client Engagement: Communicate complex technical solutions to non-technical stakeholders and deliver high-level architectural designs, presentations, and proposals. Integration and Migration: Plan and execute cloud migration strategies, integrating existing on-premises systems with GCP infrastructure . Security and Compliance: Implement robust security measures, including IAM policies, encryption, and monitoring , to ensure compliance with industry standards and regulations. Documentation: Develop and maintain detailed technical documentation for architecture designs, deployment processes, and configurations. Continuous Improvement: Stay current with GCP advancements and emerging trends , recommending updates to architecture strategies and tools. Qualifications: Educational Background: Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience). Experience: 3+ years of experience in cloud architecture, with a focus on GCP . Technical Expertise: Strong knowledge of GCP core services , including compute, storage, networking, and database solutions. Proficiency in Infrastructure as Code (IaC) tools like Terraform , Deployment Manager , or Pulumi . Experience with containerization and orchestration tools (e.g., Docker , Kubernetes , GKE , or Cloud Run ). Understanding of DevOps practices, CI/CD pipelines, and automation . Strong command of networking concepts such as VPCs, load balancing , and firewall rules . Familiarity with scripting languages like Python or Bash . Preferred Qualifications: Google Cloud Certified – Professional Cloud Architect or Professional DevOps Engineer . Expertise in engineering and maintaining MLOps and AI applications . Experience in hybrid cloud or multi-cloud environments . Familiarity with monitoring and logging tools such as Cloud Monitoring, ELK Stack , or Datadog . [CLOUD-GCDEPS-J25] Show more Show less

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. Are you excited by the challenge of pushing the boundaries with the latest advancements in computer vision and multi-modal Large Language Models? Does the idea of working on the edge of AI research and applying it to create industry-defining software solutions resonate with you? At Nielsen Sports, we provide the most comprehensive and trusted data and analytics for the global sports ecosystem, helping clients understand media value, fan behavior, and sponsorship effectiveness. This role will place you at the forefront of this mission, architecting and implementing sophisticated AI systems that unlock novel insights from complex multimedia sports data. We are looking for Principal / Sr Principal Engineers to join us on this mission. Key Responsibilities: Technical Leadership & Architecture: Lead the design and architecture of scalable and robust AI/ML systems, particularly focusing on computer vision and LLM applications for sports media analysis Model Development & Training: Spearhead the development, training, and fine-tuning of sophisticated deep learning models (e.g., object detectors like RT-DETR, custom classifiers, generative models) on large-scale, domain-specific datasets (like sports imagery and video) Generalized Object Detection: Develop and implement advanced computer vision models capable of identifying a wide array of visual elements (e.g., logos, brand assets, on-screen graphics) in diverse and challenging sports content, including those not seen during training LLM & GenAI Integration: Explore and implement solutions leveraging LLMs and Generative AI for tasks such as content summarization, insight generation, data augmentation, and model validation (e.g., using vision models to verify detections) System Implementation & Deployment: Build and deploy production-ready AI/ML pipelines, ensuring efficiency, scalability, and maintainability. This includes developing APIs and integrating models into broader Nielsen Sports platforms UI/UX for AI Tools: Guide or contribute to the development of internal tools and simple user interfaces (using frameworks like Streamlit, Gradio, or web stacks) to showcase model capabilities, facilitate data annotation, and allow for human-in-the-loop validation Research & Innovation: Stay at the forefront of advancements in computer vision, LLMs, and related AI fields. Evaluate and prototype new technologies and methodologies to drive innovation within Nielsen Sports Mentorship & Collaboration: Mentor junior engineers, share knowledge, and collaborate effectively with cross-functional teams including product managers, data scientists, and operations Performance Optimization: Optimize model performance for speed and accuracy, and ensure efficient use of computational resources (including cloud platforms like AWS, GCP, or Azure) Data Strategy: Contribute to data acquisition, preprocessing, and augmentation strategies to enhance model performance and generalization Required Qualifications: Bachelors of Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field 5+ years (for Principal / MTS-4) / 8+ years (for Senior Principal / MTS-5) of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision Proven experience in training deep learning models for object detection (e.g., YOLO, Faster R-CNN, DETR variants like RT-DETR) on custom datasets Experience in finetuning LLMs like Llama 2/3, Mistral, or open-source models available on Hugging Face using libraries such as Hugging Face Transformers, PEFT, or specialized frameworks like Axolotl/Unsloth Proficiency in Python and deep learning frameworks such as PyTorch (preferred) or TensorFlow/Keras Demonstrable experience with Multi Modal Large Language Models (LLMs) and their application, including familiarity with transformer architectures and fine-tuning techniques Experience with developing simple UIs for model interaction or data annotation (e.g., using Streamlit, Gradio, Flask/Django) Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow) Strong software engineering fundamentals, including code versioning (Git), testing, and CI/CD practices Excellent problem-solving skills and the ability to work with complex, large-scale datasets Strong communication and collaboration skills, with the ability to convey complex technical concepts to diverse audiences Full Stack Development experience in any one stack Preferred Qualifications / Bonus Skills: Experience with Generative AI vision models for tasks like image analysis, description, or validation Track record of publications in top-tier AI/ML/CV conferences or journals Experience working with sports data (broadcast feeds, social media imagery, sponsorship analytics) Proficiency in cloud computing platforms (AWS, GCP, Azure) and their AI/ML services Experience with video processing and analysis techniques Familiarity with data pipeline and distributed computing tools (e.g., Apache Spark, Kafka) Demonstrated ability to lead technical projects and mentor team members 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

It's about Being What's next. What's in it for you? A Data Scientist for AI Products (Global) will be responsible for working in the Artificial Intelligence team, Linde's AI global corporate division engaged with real business challenges and opportunities in multiple countries. Focus of this role is to support the AI team with extending existing and building new AI products for a vast amount of uses cases across Linde’s business and value chain. You'll collaborate across different business and corporate functions in international team composed of Project Managers, Data Scientists, Data and Software Engineers in the AI team and others in the Linde's Global AI team. As a Data Scientist AI, you will support Linde’s AI team with extending existing and building new AI products for a vast amount of uses cases across Linde’s business and value chain" At Linde, the sky is not the limit. If you’re looking to build a career where your work reaches beyond your job description and betters the people with whom you work, the communities we serve, and the world in which we all live, at Linde, your opportunities are limitless. Be Linde. Be Limitless. Team Making an impact. What will you do? You will work directly with a variety of different data sources, types and structures to derive actionable insights Develop, customize and manage AI software products based on Machine and Deep Learning backends will be your tasks Your role includes strong support on replication of existing products and pipelines to other systems and geographies In addition to that you will support in architectural design and defining data requirements for new developments It will be your responsibility to interact with business functions in identifying opportunities with potential business impact and to support development and deployment of models into production Winning in your role. Do you have what it takes? You have a Bachelor or master’s degree in data science, Computational Statistics/Mathematics, Computer Science, Operations Research or related field You have a strong understanding of and practical experience with Multivariate Statistics, Machine Learning and Probability concepts Further, you gained experience in articulating business questions and using quantitative techniques to arrive at a solution using available data You demonstrate hands-on experience with preprocessing, feature engineering, feature selection and data cleansing on real world datasets Preferably you have work experience in an engineering or technology role You bring a strong background of Python and handling large data sets using SQL in a business environment (pandas, numpy, matplotlib, seaborn, sklearn, keras, tensorflow, pytorch, statsmodels etc.) to the role In addition you have a sound knowledge of data architectures and concepts and practical experience in the visualization of large datasets, e.g. with Tableau or PowerBI Result driven mindset and excellent communication skills with high social competence gives you the ability to structure a project from idea to experimentation to prototype to implementation Very good English language skills are required As a plus you have hands-on experience with DevOps and MS Azure, experience in Azure ML, Kedro or Airflow, experience in MLflow or similar Why you will love working for us! Linde is a leading global industrial gases and engineering company, operating in more than 100 countries worldwide. We live our mission of making our world more productive every day by providing high-quality solutions, technologies and services which are making our customers more successful and helping to sustain and protect our planet. On the 1st of April 2020, Linde India Limited and Praxair India Private Limited successfully formed a joint venture, LSAS Services Private Limited. This company will provide Operations and Management (O&M) services to both existing organizations, which will continue to operate separately. LSAS carries forward the commitment towards sustainable development, championed by both legacy organizations. It also takes ahead the tradition of the development of processes and technologies that have revolutionized the industrial gases industry, serving a variety of end markets including chemicals & refining, food & beverage, electronics, healthcare, manufacturing, and primary metals. Whatever you seek to accomplish, and wherever you want those accomplishments to take you, a career at Linde provides limitless ways to achieve your potential, while making a positive impact in the world. Be Linde. Be Limitless. Have we inspired you? Let's talk about it! We are looking forward to receiving your complete application (motivation letter, CV, certificates) via our online job market. Any designations used of course apply to persons of all genders. The form of speech used here is for simplicity only. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, pregnancy, sexual orientation, gender identity or expression, or any other reason prohibited by applicable law. Praxair India Private Limited acts responsibly towards its shareholders, business partners, employees, society and the environment in every one of its business areas, regions and locations across the globe. The company is committed to technologies and products that unite the goals of customer value and sustainable development. Show more Show less

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. Are you excited by the challenge of pushing the boundaries with the latest advancements in computer vision and multi-modal Large Language Models? Does the idea of working on the edge of AI research and applying it to create industry-defining software solutions resonate with you? At Nielsen Sports, we provide the most comprehensive and trusted data and analytics for the global sports ecosystem, helping clients understand media value, fan behavior, and sponsorship effectiveness. This role will place you at the forefront of this mission, architecting and implementing sophisticated AI systems that unlock novel insights from complex multimedia sports data. We are looking for Principal / Sr Principal Engineers to join us on this mission. Key Responsibilities: Technical Leadership & Architecture: Lead the design and architecture of scalable and robust AI/ML systems, particularly focusing on computer vision and LLM applications for sports media analysis Model Development & Training: Spearhead the development, training, and fine-tuning of sophisticated deep learning models (e.g., object detectors like RT-DETR, custom classifiers, generative models) on large-scale, domain-specific datasets (like sports imagery and video) Generalized Object Detection: Develop and implement advanced computer vision models capable of identifying a wide array of visual elements (e.g., logos, brand assets, on-screen graphics) in diverse and challenging sports content, including those not seen during training LLM & GenAI Integration: Explore and implement solutions leveraging LLMs and Generative AI for tasks such as content summarization, insight generation, data augmentation, and model validation (e.g., using vision models to verify detections) System Implementation & Deployment: Build and deploy production-ready AI/ML pipelines, ensuring efficiency, scalability, and maintainability. This includes developing APIs and integrating models into broader Nielsen Sports platforms UI/UX for AI Tools: Guide or contribute to the development of internal tools and simple user interfaces (using frameworks like Streamlit, Gradio, or web stacks) to showcase model capabilities, facilitate data annotation, and allow for human-in-the-loop validation Research & Innovation: Stay at the forefront of advancements in computer vision, LLMs, and related AI fields. Evaluate and prototype new technologies and methodologies to drive innovation within Nielsen Sports Mentorship & Collaboration: Mentor junior engineers, share knowledge, and collaborate effectively with cross-functional teams including product managers, data scientists, and operations Performance Optimization: Optimize model performance for speed and accuracy, and ensure efficient use of computational resources (including cloud platforms like AWS, GCP, or Azure) Data Strategy: Contribute to data acquisition, preprocessing, and augmentation strategies to enhance model performance and generalization Required Qualifications: Bachelors of Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field 5+ years (for Principal / MTS-4) / 8+ years (for Senior Principal / MTS-5) of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision Proven experience in training deep learning models for object detection (e.g., YOLO, Faster R-CNN, DETR variants like RT-DETR) on custom datasets Experience in finetuning LLMs like Llama 2/3, Mistral, or open-source models available on Hugging Face using libraries such as Hugging Face Transformers, PEFT, or specialized frameworks like Axolotl/Unsloth Proficiency in Python and deep learning frameworks such as PyTorch (preferred) or TensorFlow/Keras Demonstrable experience with Multi Modal Large Language Models (LLMs) and their application, including familiarity with transformer architectures and fine-tuning techniques Experience with developing simple UIs for model interaction or data annotation (e.g., using Streamlit, Gradio, Flask/Django) Solid understanding of MLOps principles and experience with tools for model deployment, monitoring, and lifecycle management (e.g., Docker, Kubernetes, Kubeflow, MLflow) Strong software engineering fundamentals, including code versioning (Git), testing, and CI/CD practices Excellent problem-solving skills and the ability to work with complex, large-scale datasets Strong communication and collaboration skills, with the ability to convey complex technical concepts to diverse audiences Full Stack Development experience in any one stack Preferred Qualifications / Bonus Skills: Experience with Generative AI vision models for tasks like image analysis, description, or validation Track record of publications in top-tier AI/ML/CV conferences or journals Experience working with sports data (broadcast feeds, social media imagery, sponsorship analytics) Proficiency in cloud computing platforms (AWS, GCP, Azure) and their AI/ML services Experience with video processing and analysis techniques Familiarity with data pipeline and distributed computing tools (e.g., Apache Spark, Kafka) Demonstrated ability to lead technical projects and mentor team members 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

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

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. What We’re Looking For : REQUIRED SKILLS/QUALIFICATIONS 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

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

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

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. What We’re Looking For : REQUIRED SKILLS/QUALIFICATIONS 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

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