Applied Research Engineer, Chip Design

Details

NVIDIA is seeking a world-class engineer to drive applied research at the intersection of AI and ASIC design. Large language models, coding agents, and agentic AI are transforming chip design, and this role focuses on applying advanced AI to NVIDIA's real ASIC design flows and delivering solutions that land in real silicon on real schedules.

Responsibilities

• Apply LLMs, coding agents, and agentic systems to core ASIC design problems, including RTL generation, design and formal verification, PPA prediction, and optimization.
• Use LLMs, reinforcement learning, RLHF/RLAIF, post-training, evaluation, graders, synthetic data, model training, coding agents, tool-using agents, and production ML systems.
• Deliver against NVIDIA's internal chip design schedules and activities, with success measured by accelerating ASIC team workflows.
• Build robust data-generation systems, including synthetic data, and develop meticulous evaluation methodologies to distinguish working systems from demos and determine what to automate next.
• Integrate coding agents and agentic AI into EDA and validation flows, including simulation, regressions, waveform and log analysis, and script generation.
• Develop models and research harnesses on top of open-source foundations, iterating rapidly from prototype to production.
• Partner with NVIDIA's internal Nemotron team to improve models using domain-specific data, feedback, and post-training, while feeding ASIC design expertise back into the models.

Requirements

• Master's degree, PhD, or equivalent experience in Computer Science, Electrical or Computer Engineering, or a related field.
• 8 or more years of proven industry experience.
• Domain and technical expertise in front-end ASIC design, verification, and timing, combined with project experience applying agentic AI to chip design and optimization problems.
• Track record of driving ideas from conception through experimentation to production.
• Hands-on experience building LLM-based agents or AI tooling that real users depend on, including context engineering, tool integration, orchestration, failure analysis, and evaluation.
• Experience with custom model training, fine-tuning, or post-training, including SFT, RLHF, or DPO, using proprietary technical data.
• Experience building and maintaining infrastructure such as Docker, Slurm, and CI/CD systems.
• Excellent self-motivation, creativity, and passion for applied research.
• Strong collaboration skills and the ability to work effectively within a team.
• Excellent written and verbal communication skills, with experience presenting and explaining complex technical work.

Compensation and Benefits

The base salary range is $192,000–$304,750 for Level 4 and $224,000–$356,500 for Level 5. Compensation is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. Applications will be accepted at least until July 27, 2026.