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NVIDIA

Designs the chips and software that power AI

Applied Research Engineer - Chip Design

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A Master of Science or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent experience.
  • At least 8 years of industry experience.
  • Expertise in front-end ASIC design, verification, and timing, combined with project experience applying agentic AI to chip design and optimization and a record of taking ideas from conception through experimentation to production.
  • Hands-on experience building LLM-based agents or AI tooling used by real users, including context engineering, tool integration, orchestration, and failure analysis, with a focus on evaluation.
  • Experience with custom model training, fine-tuning, or post-training (SFT, RLHF/DPO) over proprietary technical data.
  • Experience building and maintaining infrastructure such as Docker, Slurm, and CI/CD.
  • Written and verbal communication skills, including experience presenting and explaining complex technical work.
  • Ability to collaborate effectively within a team.

Responsibilities

  • Apply LLMs, coding agents, and agentic systems to core ASIC design problems, including RTL generation, design and formal verification, and PPA prediction and optimization.
  • Deliver against internal chip design schedules and activities, measured by how much faster ASIC teams move.
  • Build robust data generation, including synthetic data, and evaluation methodologies that distinguish working systems from demos; use evaluation to 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, to help engineers handle complex tasks and reduce ramp time.
  • Develop models and research harnesses on open-source foundations, iterating from prototype to production to advance chip design.
  • Partner with the internal Nemotron team to improve models with domain-specific data, feedback, and post-training, and feed ASIC-design expertise back into the models.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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