ChipAgents Logo

ChipAgents

Research Scientist

Posted 10 Days Ago
Be an Early Applicant
In-Office
San Jose, CA, USA
150K-350K Annually
Senior level
In-Office
San Jose, CA, USA
150K-350K Annually
Senior level
Conduct research on AI-assisted EDA, train and deploy large language models at scale, design and benchmark agentic AI systems, translate research into production features, collaborate with cross-functional teams, and publish research where appropriate.
The summary above was generated by AI
About ChipAgents

ChipAgents is redefining the future of chip design and verification with agentic AI workflows. Our platform leverages cutting-edge generative AI to assist engineers in RTL design, simulation, and verification, dramatically accelerating chip development. Founded by experts in AI and semiconductor engineering, we partner with top semiconductor firms, cloud providers, and innovative startups to build intelligent AI agents. The company is a Series A company backed by tier-1 VC firms. ChipAgents is deployed in production to companies that have shipped 16B chips.

Position Overview

We are seeking Research Scientists with deep expertise in AI and machine learning to pioneer the next generation of AI-assisted electronic design automation. In this role, you'll conduct research that directly impacts chip designers, working at the intersection of cutting-edge AI and real-world semiconductor workflows. You'll train and deploy large language models at scale, architect intelligent agent systems, and transform research breakthroughs into production-ready tools used by leading hardware companies.

Key Responsibilities
  • Conduct research in AI-assisted EDA, focusing on practical solutions that accelerate chip design and verification workflows.

  • Train and deploy large language models using substantial compute resources, optimizing for both performance and real-world applicability.

  • Design, build, and benchmark agentic AI systems using state-of-the-art LLMs and proprietary in-house models.

  • Translate research innovations into production-ready features that integrate seamlessly into hardware engineering workflows.

  • Collaborate with cross-functional teams to identify high-impact research directions based on customer needs and field deployment learnings.

  • Publish findings and contribute to the broader AI and EDA research communities where appropriate.

Qualifications
  • Degree in Computer Science, Machine Learning, Electrical Engineering, or a related field (or equivalent research experience).

  • Strong background in large language models, deep learning, and modern ML frameworks (e.g., PyTorch, JAX).

  • Experience with AI agent architectures, autonomous systems, or multi-agent workflows.

  • Familiarity with electronic design automation (EDA) tools, RTL design, or hardware-software co-design is a strong plus.

  • Strong programming skills in Python and experience with large-scale model training infrastructure.

  • Ability to balance research rigor with pragmatic engineering to deliver real-world impact.

Why Join Us
  • Shape the future of how AI accelerates chip design and verification.

  • Work directly with the world's leading semiconductor and AI hardware companies.

  • Access to significant compute resources and real-world deployment opportunities for your research.

  • Be part of a high-impact, mission-driven team backed by tier-1 VC firms.

What we offer
  • $150K/yr – $350K/yr + Offers Equity. We are open to discuss above-scale compensation with exceptional candidates on a case-by-case basis.

  • Unlimited PTO and full benefits (medical, vision, dental, 401k).

  • Two engineering-centric offices with free parking, private gym, and free lunch, drinks and snacks.

 

Similar Jobs

17 Days Ago
Hybrid
2 Locations
160K-220K Annually
Senior level
160K-220K Annually
Senior level
Artificial Intelligence • Healthtech • Logistics • Social Impact • Software • Telehealth
Lead and conduct ML research aligned to Sprinter Health's strategy: define research agenda, design rigorous experiments, develop novel methods and evaluations, publish and patent findings, translate research into production-ready tools, and collaborate with clinicians and cross-functional teams to validate and deploy clinically robust AI solutions.
An Hour Ago
In-Office
San Francisco, CA, USA
Mid level
Mid level
Artificial Intelligence • Machine Learning • Generative AI
Join the Personalization-Memory team to research and implement long-horizon memory and personalization for frontier models. Own research agenda, build evaluations, design and debug code across the research stack, and collaborate with product and engineering to translate research into product impact.
Top Skills: Agentic SystemsLong-Horizon EvaluationMemory ArchitecturesPost-TrainingReinforcement Learning
5 Hours Ago
In-Office
Palo Alto, CA, USA
Senior level
Senior level
Healthtech • Analytics • Biotech • Pharmaceutical
Work directly with the CEO on exploratory, high-risk research projects in genomics; collaborate with other scientists; advise leadership on cutting-edge technologies; communicate complex scientific concepts to non-scientific audiences; prepare summaries and provide publications/product development history.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account