Top Tech Jobs & Startup Jobs

Research and implement GPU-acceleration techniques for high-performance databases and ETL. Analyze and optimize data-intensive workloads, collaborate with hardware, systems, and research teams to influence next-generation architectures and programming models, and publish/share findings with customers and the community.

Research and develop techniques to accelerate large-scale applications on advanced CPU platforms. Analyze and optimize database and analytics workloads for CPU performance, collaborate with internal and external experts, publish findings, and influence next-generation hardware/software design.

Conduct and publish advanced research in vehicle autonomy, developing algorithms and systems (agent behavior, end-to-end architectures, closed-loop training, safety assurances). Collaborate with internal product teams and external researchers to transfer research into production, open-source results, and present at top conferences.

Lead a team of performance engineers to optimize complex workloads on NVIDIA's CPUs and GPUs, driving technical excellence and innovation while mentoring team members and collaborating with cross-functional partners.

Lead research and engineering of large-scale multimodal AV foundation models and RL-based driving policies. Build and optimize distributed training pipelines, GPU-accelerated simulation and sim-to-real transfer, improve cluster and GPU utilization, and collaborate to deploy models to production and publish top-tier research.

Provide advanced technical support for NVIDIA InfiniBand, NVLink and GPU-based HPC/AI infrastructure. Troubleshoot installations, networking and interoperability issues on multi-distro Linux, reproduce and resolve customer problems, use packet analysis and cluster tools, and collaborate with engineering, marketing, and support teams to improve processes and documentation.

Design and implement manufacturing processes for AI client/automotive/embedded boards and systems. Provide manufacturability feedback to design, define test requirements, support NPI bring-up, validation, characterization, and production ramp. Lead prototype bring-up, failure verification, manufacturing test planning, DOE execution, and cross-functional process improvements at global manufacturing sites.

Lead physical design and implementation of SOC devices, focusing on methodologies, automation, and chip development processes including timing closure and verification.

As a Principal Engineer, you will enhance the CUDA Driver and collaborate with teams to improve GPU capabilities for various computational tasks, focusing on AI and deep learning workloads.

Design and evaluate routing policies for LLM traffic, build and run agentic benchmarks, produce calibration data and routing profiles, contribute code and docs to open-source, and collaborate across engineering teams to integrate optimized inference software into NVIDIA's serving stack.