Top Machine Learning Jobs in Pune

Design, build, and deploy ML and AI models using large structured and unstructured datasets. Develop and automate ETL/data pipelines, improve data quality, and create AI-enabled product features (NLP, deep learning, generative AI). Collaborate with product and engineering to productionize intelligent solutions that drive product usage and adoption.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Lead the development of generative AI systems, overseeing multi-agent AI architectures, machine learning pipelines, and implementing responsible AI practices. Drive innovation in AI applications using various frameworks and databases while managing cross-functional teams.

Develop statistically effective algorithms and apply machine learning, deep learning, and generative AI techniques to high-dimensional problems. Use hypothesis testing, data mining, and big-data tools to identify trends, build predictive models and recommender systems, collaborate with clients and stakeholders, and evaluate emerging datasets and technologies for scalable analytical solutions.

The Senior Technical Program Manager will drive execution across AI, data, and engineering initiatives, ensuring alignment, delivery rigor, and risk management.

The Engineering Lead will design and implement technical features, work on ML pipelines, and mentor engineers while ensuring high-quality deliverables. This role requires collaborating with teams and managing the ML lifecycle for business value.

The Director of Data Platform Engineering will oversee the data infrastructure, manage relational databases, lead AI integration, and ensure data governance while fostering a collaborative team environment.

Perform static and dynamic malware analysis, develop detections and protections, analyze IOCs, validate AI/ML outputs, build automation tools, and publish threat research.

The role involves conducting AI research, teaching AI-related courses, collaborating on healthcare data modeling, and securing external funding, while mentoring students.

The Postdoctoral Research Associate will lead research in structural health monitoring of transportation infrastructure, manage research activities, analyze data, and support proposal writing and public engagement events.

Conduct interdisciplinary AI research focused on healthcare, develop and teach related courses, collaborate on complex healthcare data analysis, and secure funding.

Design, develop and deliver enterprise-grade Pega solutions. Collaborate across teams, ensure code quality, integrations (REST/SOAP/Kafka/MQ), performance tuning, security, DevOps pipeline ownership, production stability and lead distributed Agile teams.

Use data analytics and machine learning to extract insights from large transactional datasets, build and maintain data pipelines, develop predictive models, produce MI and visualizations (Power BI/Tableau), support automation and model-driven decision support for payment screening and sanctions, and partner with stakeholders to mitigate financial crime risk.

Lead data science initiatives using advanced statistical techniques and machine learning to produce actionable insights. Partner with cross-functional teams to design data-driven solutions, manage and ensure integrity of large datasets, develop predictive models to forecast trends, and communicate results to stakeholders while staying current on emerging technologies.

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.

Learn to design and build dashboards, reports, and data models using Power BI and Microsoft Fabric. Assist with SQL-based datasets, Python-based data modeling and ML fundamentals, documentation, and analytics standardization while collaborating with global data engineers and analysts.

The role focuses on developing analytical data science products, implementing algorithms for insights, and expertise in deep learning frameworks.

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.

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).

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.