Applied Research Engineer, Chip Design
NVIDIA· Research Staff Member
Santa Clara, CA$192k - $304.8kFull-timePosted 3mo ago
About the role
Applied research engineer role at the intersection of AI and ASIC design, focusing on applying AI/agentic systems to ASIC design workflows and pushing production-ready capabilities.
Responsibilities
- Apply LLMs, coding agents, and agentic systems to core ASIC design problems: RTL generation, Design and Formal verification, PPA prediction and optimization.
- Hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evaluation, graders, synthetic data, model training, coding agents, tool-using agents, and production ML systems
- Deliver against internal chip design schedules and activities; success measured by acceleration of ASIC teams’ progress
- Build robust data generation (including synthetic data) and meticulous evaluation methodology to separate working systems from demos and guide automation decisions
- Wire coding agents and agentic AI into EDA and validation flows — simulation, regressions, waveform and log analysis, script generation
- Push the limits of what's possible in chip design with models and research harnesses on open-source foundations, iterating prototype to production
- Partner with NVIDIA’s internal Nemotron team to improve models with domain-specific data, feedback, and post-training
Qualifications
- MS or PhD or equivalent in Computer Science, Electrical/Computer Engineering, or related field
- 8+ years of proven industry experience
- Domain and technical expertise in front-end ASIC (design, verification, timing) with project experience applying agentic AI to chip design and optimization, with end-to-end development from conception to production
- Hands-on experience building LLM-based agents or AI tooling that real users depend on (context engineering, tool integration, orchestration, failure analysis) with a focus on evaluation
- Experience with custom model training, fine-tuning, or post-training (SFT, RLHF/DPO) over proprietary technical data
- Excellent self-motivation, creativity, and a passion for applied research; strong collaboration skills and teamwork
- Experience building and maintaining infrastructure (Docker, Slurm, CI/CD, etc.)
- Excellent written and verbal communication, with proven experience presenting and explaining complex technical work
Skills
Required:LLM-based agents / AI toolingAgentic AI integration in EDA/validationData generation and evaluation methodologyFront-end ASIC (design, verification, timing)Model training / fine-tuning / post-trainingInfrastructure and toolingCommunication and collaboration
Benefits
- Equity
- Benefits (see NVIDIA benefits page)
Last updated Jul 24, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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