Top Tech Jobs & Startup Jobs in Chennai

The role involves managing end-to-end operations including warehousing, logistics, inventory management, and SAP transactions while optimizing costs and improving processes across multiple locations in India.

Design, train, optimize, and productionize deep learning models for speech/audio and computer vision. Build scalable training pipelines, perform model inference optimization, integrate models into production services, monitor performance, and collaborate with software and product teams to deliver low-latency, reliable ML features.

Lead Data Operations globally: run the Data Academy, manage regional Data Operations Leads, set SLAs and SOPs for the Data Desk, design enablement and recruitment systems, define technical standards (SQL, LookML, AWS), and drive automation with engineering while providing hands-on mentorship and escalation oversight.

The Infrastructure Engineer will enhance IAC, CI/CD pipelines, and scalable cloud infrastructure while collaborating with multiple teams on incident response and observability solutions.

Design, build, and maintain scalable ETL/ELT and real-time data pipelines on AWS. Manage Airflow DAGs, Kafka ingestion, Redshift optimization, data quality checks, API integrations, and cost optimization while collaborating with BI for reporting needs.

The Cyber Risk Analyst will drive cyber security audits, manage vendor security reviews, and support business continuity and compliance frameworks.

The Lead Analyst will enhance credit risk frameworks, optimize financial performance, and translate data insights into strategic decisions while managing end-to-end analytical projects.

The role involves managing the global marketing strategy for PAYG phones, focusing on brand positioning, demand generation, and cross-functional collaboration across multiple markets.

The Senior Product Manager will lead product roadmaps, mentor teams, manage execution, collaborate with engineering, and monitor product performance across multiple regions.

Design and build scalable backend systems and AI-powered solutions (LLMs, RAG, retrieval, agents). Own projects end-to-end, optimize performance, drive AI engineering standards, mentor engineers, and integrate AI with enterprise systems.