Top AI & Machine Learning Jobs in Pune, MH

Design and build production-grade AI applications embedding ML/LLM capabilities. Integrate trained models into APIs, services, UIs, and workflows. Operationalize models (versioning, deployment, monitoring), implement guardrails, ensure security/privacy/compliance, apply bias mitigation and explainability, and mentor team members on AI engineering best practices.

Design, build, and maintain scalable data pipelines and cloud data platforms to support AI/ML workloads. Deploy, monitor, and operationalize machine learning models, implement CI/CD and MLOps, ensure data quality, scalability, and governance while collaborating with data scientists, engineers, and stakeholders.

Lead and grow engineering teams to design, build, and operate scalable data and AI platforms. Own end-to-end delivery, architecture, and operational excellence for data pipelines, AI-enabled services, and platform capabilities while ensuring security, reliability, governance, and cross-functional alignment.

Manage and mentor a cross-functional engineering team to design, build, and deploy analytics and AI-driven full-stack solutions. Lead technical direction, architect scalable data pipelines and APIs, collaborate with product and design, and champion cloud-native, testable, production-grade applications while promoting continuous improvement and responsible AI practices.

Lead and grow a data science team to deliver predictive and ML-driven insights. Partner with business and engineering to build production-ready models, enforce model governance, ensure explainability, and measure business impact while driving continuous improvement.

Join the AI Innovation at Scale team to design and execute test strategies, perform white-box and black-box testing, validate data using Impala and Spark, monitor Spark job execution, collect logs, analyze quality data, and work with stakeholders to resolve issues and improve QA processes.

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.