Top Tech Jobs & Startup Jobs

Lead end-to-end sourcing, procurement, and delivery of infrastructure and circuits for global PoP deployments. Manage carrier and data center relationships, negotiate contracts and SLAs, oversee site readiness, equipment logistics, capacity planning, testing, and documentation to ensure on-time, compliant PoP turn-up and lifecycle activities.

Lead end-to-end program outcomes across multiple silicon programs from architecture through tape-out and silicon correlation. Own schedules, manage headroom and resources, prioritize and steer engineering, align cross-boundary teams, translate and mitigate technical risk, and implement durable process improvements to raise execution standards and predictably deliver at scale.

Drive go-to-market and enterprise software sales for NVIDIA Agentic AI with Lenovo, packaging NVIDIA assets with Lenovo solutions, co-marketing and co-selling across direct and partner channels. Build technical understanding of accelerated computing and cloud-native stacks, develop ecosystem partnerships, lead three-way sales and marketing plans, and provide thought leadership at industry and customer events.

Lead performance engineering for AV and robotics workloads: engage customers, develop parallel algorithms and GPU-optimized libraries, profile and tune GPU kernels, optimize distributed transformer communication using NCCL/NVSHMEM and interconnect strategies, and collaborate with architecture and system teams to influence next-generation hardware and software.

Design, implement, and operate large-scale, high-performance storage clusters for AI/ML workloads. Develop monitoring, alerting, automation, and capacity management. Optimize latency, throughput, caching, compression, deduplication, tiering, and data placement. Support lifecycle from design to production, participate in on-call rotations, incident response, and continuous improvement with AI-driven automation and predictive analytics.

Define technical vision and architecture for vehicle dynamics simulation. Implement production C++ interfaces, model-selection and parameter-identification workflows, translate control commands to time-aligned motion, validate and calibrate models using measured logs and test data, set standards and release gates, mentor engineers, and collaborate across planning, controls, simulation, and product teams.

Design and develop core components and performant frameworks for an autonomous driving platform, interfacing with vehicle sensors, optimizing parallel/GPGPU code (CUDA), performing in-vehicle tests and data collection, writing production C++ code, and ensuring quality and safety compliance.

Own and scale the end-to-end cloud execution pipeline for simulation assets, deploying GPU-aware containers and multi-GPU runtimes, implementing structural and runtime validation, AI-driven remediation, observability, CI/CD, and artifact pipelines to ensure reliable, automated cloud validation of simulation assets.

Work on performance and scalability of Kubernetes-based accelerated runtimes for AI, from orchestration to hardware. Design upstream Kubernetes changes, improve container startup and encrypted container performance, build large-scale simulation and CI-based tests, collaborate with researchers and upstream communities, and present results publicly.

Design, implement, and maintain Compute Sanitizer memory-checking tools for NVIDIA GPUs across Linux, Windows, Android and embedded RTOS. Collaborate with compiler, driver and architecture teams, write and review low-level, performant code, create tests, document designs, estimate work, and mentor junior engineers.