Top Machine Learning Jobs in Pune

Create and review realistic, domain-specific robotics tasks in Hindi; apply scoring rubrics; evaluate AI and human responses for accuracy, regulatory alignment, and professional quality; and produce gold-standard solutions and expert feedback.

Create and review realistic, locale-specific robotics and natural sciences tasks in Tamil to evaluate AI systems; apply scoring rubrics, review and score submissions for accuracy and regulatory alignment, and produce gold-standard solutions and expert feedback.

Lead design and implementation of ML tools for scenario classification, anomaly detection, sensor data quality, behavior analytics, and automated reporting. Build scalable pipelines and automated data curation for camera, radar, and LiDAR; create SIL/HIL replay interfaces, ground-truthing and annotation tools, and offline benchmarking. Integrate ML modules into simulation, HIL/SIL, and CI/CD ecosystems, implement reproducible workflows (Docker, CI/CD, artifact versioning, automated tests), monitor model/data quality and mentor junior engineers while collaborating with verification and perception teams.

Lead design and implementation of ServiceNow ITOM Event Management and Dynatrace observability to reduce alert noise, automate incident correlation and remediation, implement observability-as-code via APIs/CI-CD/Terraform, leverage AI/ML for root-cause and predictive monitoring, and track KPIs like MTTR and alert reduction.

Lead requirements gathering, process analysis, and documentation for Legal IT systems. Support design, testing, training, stakeholder communication, and project delivery. Identify automation/AI opportunities and monitor KPIs to improve contract lifecycle efficiency and compliance.

Lead a Pune-based analytics team to deliver and govern finance BI reporting and AI/ML analytics. Manage intake, prioritize initiatives, build standardized dashboards and KPIs, ensure data governance and model lifecycle practices, champion ML/LLM automation, reduce manual work, and drive decision-ready insights for global finance stakeholders.

As an AI Data Expert, you'll evaluate AI-generated outputs, review text, analyze multimedia, and provide structured feedback based on cultural standards.

The Senior Manager, Machine Learning leads the Conversation Memory team, focusing on developing foundational AI features, ensuring operational excellence, mentoring engineers, and managing project timelines for ML solutions.

Lead development and deployment of ML/AI solutions: build models (classification, prediction, anomaly detection, NLP), prototype ML products, prepare and pipeline data, collaborate with product and engineering, deliver insights, and mentor team members.

Design, develop, and productionize machine learning and deep learning models, build scalable data and embedding pipelines, implement RAG/LLM-based applications using LangChain/LlamaIndex, integrate models as APIs, and optimize model performance and scalability for product integration.

Lead development and production deployment of AI/ML models focused on personalization, recommendations, segmentation, and predictive analytics. Collaborate with data engineering and development teams to ensure data readiness, integrate models into production (real-time systems like Kafka), apply AIOps to monitor performance, and mentor an AI/ML team.

Lead design, build and maintain data architectures, pipelines, warehouses and lakes; develop processing and analysis algorithms; collaborate with data scientists to deploy ML models; manage risk and lead teams or projects.

The ROR Developer will focus on software engineering practices, design, data structures, algorithms, and deliver projects with responsibility, while keeping pace with industry trends.

The Data Scientist will leverage critical thinking and data analysis skills to develop Machine Learning models for detecting financial crime risks and synthesizing data requirements.

Lead end-to-end AI solutions for clients, manage project delivery and people, partner with sales for business development, collaborate with engineering/MLOps/DevOps, ensure data quality, model training, tuning, deployment, monitoring, and provide executive updates on status and risks.

Evaluate and author high-quality computer science content to improve AI model reasoning and accuracy. Analyze complex CS problems, create scenarios/datasets, review AI outputs for correctness, and collaborate remotely to refine guidelines and documentation.

As a Junior-Midlevel Developer, you will develop, maintain, and enhance an AI-powered education platform, collaborating with teams to build software and optimize performance.

Analyze and interpret complex data to drive business decisions. Design and deliver reports and dashboards using SAP Fiori and SAP Analytics Cloud. Improve data quality via profiling, catalogs, ML techniques, and cleansing rules. Collaborate with stakeholders, document processes, mentor junior staff, and integrate analytics into governance and technology initiatives.

Lead product strategy and execution for Communications within Lending. Define OKRs and roadmaps, collaborate with engineering, design, ML, risk and compliance, use data to drive decisions, and deliver omni-channel communication features that improve members' financial health.

Design, build, and operationalize ML and deep learning solutions including supervised/unsupervised models and LLM fine-tuning. Implement RAG, vector DBs, prompt engineering, deploy on cloud (AWS/Azure), set up experiments, and present technical findings while partnering with business stakeholders.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.

Build, maintain, and improve programming solutions and AI/ML applications to automate workflows, analyze operational data, and optimize processes. Collaborate with cross-functional teams, maintain operational systems, and document technical procedures to support reliable, scalable operations.

Evaluate AI-generated technical content, craft and answer advanced ML/AI prompts, assess model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.