Top Tech Jobs & Startup Jobs in Austin, TX

Maintain and optimize GeForce NOW infrastructure, develop and improve CI/CD pipelines and observability for content services, optimize performance/cost/reliability, collaborate with engineering teams, and participate in on-call rotations to resolve service issues.

Design and implement developer tools for GPU-based 3D graphics and neural rendering. Improve existing tooling, collaborate with compiler/driver/research teams, write high-performance C/C++ code, document designs, estimate tasks, and develop test plans with QA.

Drive physical design of high-frequency, low-power CPUs/GPUs/SoCs at block, cluster, or full-chip level with emphasis on netlist quality: equivalence checking/formal verification, CDC and MTBF analysis, logic synthesis, timing convergence, STA, constraint generation/management, and ECO implementation. Use industry-standard EDA tools and scripting to debug and improve flows.

Develop and integrate full-system functional models for CPU architectures, support CPU architects, and enhance system software for performance modeling.

Design, develop, test, and optimize system software for next-generation ARM SoCs in pre- and post-silicon phases. Analyze system-wide performance bottlenecks, recommend HW/SW policies, perform competitive workload comparisons, and drive full-stack adoption of performance optimizations across NVIDIA software and OSS SDKs.

Drive physical design for CPUs, GPUs, and SoCs focusing on netlist-related tasks, logic synthesis, and timing closure. Help in ECO generation.

The Senior LLVM Compiler Engineer will contribute to upstream LLVM development, lead design discussions, and ensure high-quality compiler solutions in collaboration with open-source communities.

Serve as technical lead between NVIDIA and hyperscale CSPs on GPU firmware and system software. Drive firmware update orchestration, recovery procedures, multi-GPU coordination, telemetry/health monitoring, and incorporate CSP feedback into NVIDIAs roadmap to improve fleet-scale manageability and reliability.

Develop core components of the CUTLASS platform, contribute to the MLIR-based backend compiler stack, and author example kernels while collaborating with GPU architecture teams.

Lead technical engagements with cloud service providers on rack-scale system software and firmware. Drive architecture alignment, integration readiness, error handling and recovery, health telemetry, firmware orchestration, and serviceability. Capture CSP feedback, influence NVIDIA system software design, improve tooling and tests, and mitigate execution risks through early collaboration.