AI Research Engineer - Applied Scientist Compilers

Details

NVIDIA's GPUs are at the core of modern AI infrastructure, from training large-scale models to running inference in production. This position focuses on software and compiler engineering that enable GPU acceleration for modern machine learning models. The team develops AI-based compiler solutions that integrate with NVIDIA's software stack.

Responsibilities

• Help trailblaze company efforts in applying AI within conventional compilation pipelines.
• Design and implement AI-based technology addressing core problems of low-level GPU programming.
• Build training pipelines for supervised fine-tuning and reinforcement learning (RL/RLHF-style or policy optimization variants).
• Define model inputs/outputs over low-level compiler representations.
• Develop evaluation frameworks to measure code quality, runtime, compile-time overhead, and correctness.
• Intelligent (domain/task-based) prompt engineering.
• Collaborate with compiler engineers to integrate learned policies into production toolchains.
• Prototype and iterate on model architectures, prompts, and fine-tuning strategies for scheduling and allocation tasks.
• Create datasets from compiler traces, optimization passes, and target-specific performance signals.
• Apply RL techniques to optimize for downstream objectives (performance, spill reduction, instruction-level parallelism, etc.) and run rigorous experiments, ablations, and benchmarking across workloads and hardware targets.

Requirements

• M.S. or PhD degree in Computer Engineering, Computer Science, or a related technical field (or equivalent experience).
• 5+ years of experience building AI/ML systems.
• Strong software engineering skills in Python and at least one systems language (C++ preferred).
• Hands-on experience training/fine-tuning large models (Transformers, PEFT/LoRA, distributed training).
• Solid understanding of machine learning fundamentals and experimentation best practices.
• Experience with reinforcement learning (e.g., policy gradients, actor-critic, offline RL, bandit-style optimization).
• Knowledge of prompt-engineering techniques.
• Ability to work across research and engineering, from prototype to production.

Preferred / Ways to Stand Out

• Distributed training/inference at scale.
• Experience working with the NVIDIA NeMo framework.
• Understanding of GPU performance, experience with benchmarking suites and performance profiling tools.
• Formal methods or static analysis familiarity for correctness guarantees.
• CUDA programming experience.

Compensation & Benefits

• Base salary range: 152,000 USD - 241,500 USD (base salary will be determined based on location, experience, and pay of employees in similar positions).
• Eligible for equity and benefits (link provided in original posting).

Additional Information

• Applications for this job will be accepted at least until April 26, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and states non-discrimination in hiring and promotion practices.