Senior AI Compiler Engineer - Applied Research

Details

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.
• Solid 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.

Ways to stand out from the crowd

• Distributed training/inference at scale (Megatron, NeMo, vLLM, Triton).
• Experience working with the NVIDIA training stacks.
• Fundamentals of construction of 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

• Eligible for equity and a generous benefits package.