4 days ago
Responsibilities
- Design, build, and optimize intelligent low-level compiler systems, including compiler-oriented agents, multi-step transformation workflows, tool use, memory, and orchestration.
- Develop systems for reasoning about low-level intermediate representations, code generation, optimization passes, scheduling, numerical precision, and GPU-centric performance tradeoffs.
- Build data, environments, verification, reward, and evaluation systems to improve compiler quality, numerical correctness, robustness, and performance.
- Develop numerical validation, differential testing, regression detection, and correctness-verification infrastructure for generated or transformed code.
- Co-design compiler and verification workflows across models, inference, compiler pipelines, runtimes, libraries, kernels, and GPUs.
- Collaborate with compiler, CUDA, library, runtime, and hardware teams to integrate compiler, agentic, and verification capabilities into NVIDIA products.
- Drive performance analysis and optimization for generated or transformed code with emphasis on correctness, scalability, and deployment.
Requirements
- Bachelor’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent experience; an MS or PhD is preferred.
- At least 5 years of relevant industry or academic experience in compilers, AI systems, numerical computing, verification, high-performance computing, or related areas.
- Hands-on experience in compiler implementation, program analysis, code generation, optimization, low-level performance engineering, or correctness infrastructure.
- Experience with agent systems, coding agents, compiler automation, numerical analysis, program verification, differential testing, or formal or semi-formal validation methods.
- Strong C/C++ and Python programming skills and solid software engineering fundamentals.
- Experience with GPU programming and performance optimization using CUDA or comparable accelerator platforms.
- Ability to work across model-driven workflows, compiler infrastructure, runtime systems, and hardware-aware optimization.
- Expertise in LLVM, MLIR, PTX, Triton, AI-assisted compilation, numerical validation, equivalence checking, autotuning, compiler verification, GPU systems, or numerical performance is preferred.
- Publications, open-source leadership, benchmark results, or deployed systems in compilers, numerical computing, verification, formal methods, agentic AI, high-performance computing, AI systems, or programming systems are valued.
Benefits
- Highly competitive salaries and a comprehensive benefits package.
- Equity and benefits eligibility.
- Applications are accepted at least until November 6, 2026.
- This posting is for an existing vacancy.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.