Senior AI Compiler Engineer - Applied Research

About the role

NVIDIA is seeking an AI Research Engineer / Applied Scientist specializing in compilers and low-level optimization to contribute to groundbreaking AI compiler technologies. The ideal candidate will design and implement AI-based solutions for complex low-level GPU code generation, define model inputs using low-level compiler representations, and apply reinforcement learning techniques to optimize compilers.

Responsibilities

• Design and implement AI-based technology addressing core problems of low-level GPU code generation.
• Build SFT and RL training pipelines.
• Define model inputs using low-level compiler representations.
• Define, implement, and evaluate strategies for intelligent prompt engineering in compilation domain.
• Prototype and iterate on model architectures, prompts, and training strategies for NP-hard problems in optimizing compilers.
• Prepare datasets from compiler traces, optimization passes, and target-specific performance signals.
• Apply RL techniques to optimize for downstream objectives and run rigorous experiments, analysis, and benchmarking across workloads and hardware targets.
• Build rigorous benchmarks to assess code quality, correctness, and generation overhead.
• Partner with compiler engineers to integrate and ship learned policies with production toolchains.

Requirements

• M.S. or PhD degree in Computer Engineering, Computer Science related technical field (or equivalent experience).
• 5+ years of experience building AI/ML systems.
• Strong understanding of machine learning fundamentals and experimentation best practices.
• Strong software engineering skills in Python and C++.
• Hands-on experience training/fine-tuning/post-training large models.
• Experience with reinforcement learning.
• Reward modeling from non-differentiable signals (binary runtime/compile success, performance counters).
• Knowledge of prompt-engineering techniques (CoT, chaining/orchestration, context adaptation, etc).
• Ability to work across research and engineering, from prototype to production.
• CUDA programming experience and GPU performance familiarity.

Desired Skills

• Distributed training/inference at scale (Megatron, NeMo, vLLM, Triton).
• Experience working with the NVIDIA training stacks.
• Fundamentals of constructing optimizing compilers.
• Understanding of GPU performance, experience with benchmarking suites and performance profiling tools.
• Knowledge of formal methods or static analysis for correctness guarantees.

Benefits

Competitive salaries, generous benefits package, equity, and opportunities for professional growth. Applications are open until June 20, 2026.

Pay

Base salary range: $152,000 - $241,500 USD.

Schedule

Full-time.

Benefits

Comprehensive benefits package including health insurance, retirement plans, and more.

Equal Opportunity Employer

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. We highly value diversity in our workforce and welcome applications from all qualified candidates regardless of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.