NVIDIA's GPUs are at the core of modern AI infrastructure, from training large-scale models to running inference in production. That position depends on software as much as hardware, and compiler engineering is a big part of what makes it work.

We are looking for outstanding AI Research Engineer /Applied Scientist focused on Compilers /Low-level optimization to join the team and develop groundbreaking technologies in machine learning compilers and AI systems. We build innovative AI compiler solutions that work together with NVIDIA's software stack to provide comprehensive acceleration for modern machine learning models.

What you'll be doing:

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 compiler 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.

What we need to see:

M.S./PhD degree in Computer Engineering, Computer Science 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.

Ways to stand out from the crowd:

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.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous program manager with a real passion for technology, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 11, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis 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.