Top Tech Jobs & Startup Jobs in Mumbai

Lead STA execution for DPU ASICs from early design to signoff. Develop and maintain STA methodology, perform timing planning and analysis, drive closure and ECO flows, coordinate cross-team timing resolution, and ensure successful tapeout signoff.

Manage enterprise accounts to drive renewals, adoption, upsell/cross-sell and customer satisfaction. Develop strategic account plans, orchestrate cross-functional teams and partners, lead negotiations, and act as trusted advisor to achieve revenue and consumption targets.

Design, implement, and deliver security firmware for Azure server and rack infrastructure. Lead architecture, driver/bring-up, and secure firmware features; perform system-level debugging; incorporate SDL and test-driven practices; collaborate with cross-functional teams and partners to meet cloud security and production requirements.

Lead full-chip and package integration for DPU ASICs from early planning through tapeout signoff. Drive die/floorplanning, C4/microbump and RDL optimization, power domain management, vendor collaboration, integration milestones, and resolve power/integration issues across teams.

Senior Data & AI consultant responsible for designing, developing, and delivering cloud data and AI solutions on Microsoft platforms. Lead data engineering, platform modernization, ML readiness, MLOps, and Azure-based deployments while collaborating with customers and teams to drive adoption and technical excellence.

Own revenue growth for a portfolio of licensing and solution partners. Build C-suite relationships, create and execute Partner Business Plans, lead cross-functional PODs, drive renewals, co-sell, AI/Copilot and security motions, and run disciplined sales rhythms (MBR/QBR, pipeline, MCEM) to meet quarterly targets.

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 real-world data science projects using machine learning, statistics, experiments, and data exploration. Collaborate with stakeholders, produce actionable insights, validate analyses, participate in peer review, and iterate to improve products impacting millions of customers.

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.

Work on real-world software projects: design, develop, test, and improve software. Collaborate with stakeholders, learn new technologies, apply engineering principles, and enhance product reliability, performance, and observability in a team environment.