Top Tech Jobs & Startup Jobs in Pune

Lead operational reliability for enterprise and data center networks: manage incidents, ensure high availability, partner on deployments, automate toil, monitor performance, perform RCAs/postmortems, and produce documentation and knowledge-base articles to improve network operations and SLOs.

Develop and improve GPU profiling libraries and Nsight tools, design metrics and data-collection methodologies, read HW specs to design solutions, write unit tests and support multiple platforms from supercomputers to embedded systems.

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 strategic partner engagement with major Indian conglomerates to identify, design, and scale enterprise AI workloads. Build executive and technical relationships, coordinate cross-functional NVIDIA teams, run workshops and architecture reviews, develop repeatable use cases, and capture account requirements and product feedback to deliver deployable, scalable AI outcomes across cloud, data center, edge, and industrial environments.

Design, develop, optimize, debug, and maintain features for NVIDIA GPUs. Collaborate with teams, resolve customer issues, and improve documentation.

Lead interaction design across hardware, software and services. Collaborate with researchers, engineers and product teams to create journeys, IA, prototypes, specs, and design critiques that drive user-centered solutions.

Build and maintain cloud-native deployment platform: backend microservices, CRDs/operators, GitOps pipelines, staging environments, multi-cloud and bare-metal automation, CI/CD integrations, monitoring and automated remediation for zero-downtime global rollouts.

The role involves developing infrastructure for AI applications, managing deployment processes, analyzing data, and collaborating with developers to optimize automation systems in the Windows ecosystem.

Design, implement, and maintain infrastructure and CI/CD pipelines to deploy and automate local AI workloads across inference backends. Build model download and repository sync systems, implement data processing and visualizations, measure accuracy and performance, debug existing frameworks, and collaborate with developers to streamline debugging and deployment of AI applications and models.

Lead and grow a team building an on-device AI inference platform for RTX/ DGX GPUs. Drive cross-functional alignment, architect inference runtimes, optimize models and pipelines for low-latency, memory-efficient local deployment, and establish processes for system-level debugging, performance/accuracy trade-offs, and production readiness. Mentor engineers and deliver roadmap-aligned, high-quality releases.