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.

Perform asset-allocation and manager-evaluation research, bespoke portfolio and data analyses, database creation and ETL, build dashboards (Python Dash), develop quantitative models and automated reports using Python/SQL, and apply statistical modelling, ML and AI tools to support investment research and portfolio construction.

Lead architecture and delivery of production-grade GenAI full‑stack solutions using Python and React. Design scalable LLM inference, RAG and agent pipelines, integrate cloud/on‑prem deployments, enforce security/governance, drive CI/CD and QA, mentor teams, and translate business needs into technical strategy and reusable AI platforms.

Early-career role analyzing PB-scale on-chain, transactional and customer data. Perform data engineering, ETL, querying, build visualizations and ML models, translate insights for teams, manage reporting environment, secure confidential data, and troubleshoot reports/databases.

Analyze PB-scale trading, transactional, operational and customer data; build visualizations, ML models and experiments; translate findings into actionable recommendations for trading, operations, product and executives in a fast-paced environment.

Work with Product, Business, and Engineering to collect, clean, analyze data, build Python and SQL automation, contribute to internal analytics platforms, assist cloud deployments, and document technical solutions to support decision-making.

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.

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

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

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.

Develop and support secure IoT software applications, APIs, and UIs; build dashboards, ETL/data workflows, and analytics; enable ML/AI capabilities; maintain and modernize legacy code hosted on AWS.

Lead an 8-10 engineer team owning courier systems (dispatch, matching, pricing, ETA). Set technical direction, drive data-driven decisions and experiments, partner with data science, ensure reliability and scalability of low-latency distributed systems, and own hiring, performance, and operational excellence.

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.

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.

Lead advanced statistical analyses and machine learning projects, partner with cross-functional teams to design data-driven solutions, manage large datasets with governance best practices, build predictive models to forecast trends, and communicate insights to stakeholders.

Lead development of production-ready AI/ML systems focusing on computer vision and image processing. Apply generative AI and deep learning, mentor teams, drive cross-team technical decisions, and deploy solutions on cloud or on-prem pipelines.

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.

Lead design, build and maintenance of data architectures, pipelines, warehouses and lakes; enable ML lifecycle by preparing governed datasets, collaborating with data scientists, and driving data governance, lineage, access controls and analytics-ready schema design.

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 data analysis and engineering to enable data-driven decisions: investigate data quality and lineage, build automated pipelines, apply advanced analytics and ML, design interactive dashboards and reports, translate insights into business recommendations, and support governance and controls while coaching or leading team members.

This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.