Top Machine Learning Jobs in Pune

Lead a team of data scientists in developing and deploying machine learning models, ensuring code quality, documentation, and smooth industrialization of projects.

Design, build and maintain data pipelines, data warehouses and data lakes; implement processing and analysis algorithms; optimize database performance; collaborate with data scientists to deploy ML models; lead teams or projects and influence stakeholders.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

Build and maintain scalable backend services for an AI legal product: fine-tune LLMs, create data processing and document/OCR pipelines, integrate LLMs, and manage infrastructure with Terraform/OpenTofu and Docker.

Lead end-to-end data analysis: transform raw data, develop reports and dashboards (PowerBI), monitor performance and quality, implement ETL and data modeling, apply predictive modeling/NLP/machine learning, and support cross-functional data-driven decisions.

Lead design and delivery of end-to-end AI/ML and Generative AI solutions, architect scalable cloud-based platforms, integrate LLM/RAG/agentic systems, implement MLOps and governance, and mentor teams while driving AI strategy with stakeholders.

One-year, full-time fellowship supporting design, delivery, and evaluation of interventions for smallholder farmers. Duties include research and analysis, pilot design, field implementation, M&E, and cross-team collaboration with heavy mentorship and rotating in-country placements.

The Data Engineer will build and maintain data architectures, pipelines, warehouses, and lakes, ensuring data accuracy and security. They will collaborate with data scientists and oversee operational processes within the team, driving continuous improvement.

Perform static and dynamic malware analysis, develop automation and detection signatures, conduct IOC/reputation analysis, validate AI/ML model outputs, and produce threat research and tooling to protect and scale Zscaler's platform.

As a Customer Support Engineer, you will resolve customer technical issues, perform installations, upgrade systems, and support field services while maintaining customer relationships.

Lead the India-based Oncology Market Access & Insights (MAI) portfolio, driving delivery, prioritization and transformation (AI, workflow redesign). Act as primary liaison with global BU leadership, integrate primary research with analytics, enable cross-functional alignment, and manage a high-performing distributed team to deliver insight-driven access, pricing and launch solutions.

Lead a 15+ person analytics team to build customer-understanding models (segmentation, propensity, risk stratification, KOL identification, content-affinity) and data products powering commercial activation. Translate business questions into validated ML/statistical solutions, orchestrate cross-functional pods, prioritize work with business units, and drive GenAI and analytics innovation across pharma commercial datasets (claims, EMR, Rx, CRM).

PhD intern will research and prototype AI techniques for Azure SQL Database, analyze algorithms on large datasets, build scalable ML systems, collaborate with researchers and product teams, and contribute to technology transfer and publications.

Work on machine learning research and prototypes: analyze algorithms on large datasets, design experiments, prepare and clean data for modeling, and implement scalable AI system prototypes under senior guidance.

The Staff Machine Learning Engineer will architect and implement scalable GenAI platform solutions, ensuring reliability and safe AI experiences across product lines while mentoring engineers and leading technical strategies.

Design, develop, and deploy ML/AI solutions (Computer Vision, NLP, Recommendation Systems). Build and optimize models, implement scalable data pipelines and ML workflows on cloud platforms, collaborate with cross-functional teams, translate business needs into algorithms, ensure secure and performance‑optimized code, and document solutions for stakeholders.

Develop and maintain DirectX graphics drivers for NVIDIA GPUs, design new OS and GPU features, improve graphics and AI-based rendering, build AI-driven engineering automation and agent-based tooling, collaborate across teams to drive software objectives and quality improvements for gaming and graphics workloads.

Lead architecture and development of the core native iOS SDK and related apps. Own feature delivery from design to public release, write high-quality tested code, collaborate with R&D and ML teams, support customers to resolve issues, and manage priorities across large-scale, distributed projects.

Lead post-deployment operations and optimization of Agentic AI, LLM integrations, and Python-based analytical pipelines. Supervise a data science operations team, ensure secure high-availability production systems, manage integrations with enterprise systems (SAP, Salesforce, Postgres), and drive continuous improvement, monitoring, and adoption of analytics solutions.

Lead engineering projects, automation and digitization, new product qualification, and machine/process reliability. Manage budgets, timelines, root-cause troubleshooting, maintenance strategy, and integration of advanced manufacturing technologies. Mentor and develop engineering team, ensure safety and compliance, and coordinate with regional/global stakeholders to drive productivity and operational excellence.

Consult with CPG/FMCG clients on Revenue Growth Management analytics programs, focusing on pricing strategies, promotion analysis, and optimizing revenue growth while leading engagements across diverse global markets.

Design and deploy predictive models and recommendation engines for B2B distributor transaction data; clean and transform ERP-sourced datasets; produce dashboards and account-level insights to drive sales strategy; present findings to business leaders and enable scalable analytics solutions for commercial growth.

Design and own end-to-end solution architectures, translate requirements into technical designs, evaluate technologies, define integrations, guide development and DevOps teams, conduct reviews and POCs, support pre-sales, and ensure compliance with ISO standards.

Drive sales of CCTech digital transformation solutions to AEC, construction, and infrastructure clients. Prospect and manage pipeline, conduct discovery and solution positioning, support pre-sales workshops and proposals, collaborate with engineering teams, and develop strategic accounts focused on BIM, digital twin, automation, analytics, and enterprise integrations.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.