We are hiring Research Engineers to apply machine learning to electronic design automation (EDA). Power, performance, and area are the central tradeoffs in chip design, and getting them right takes deep expertise and long iterations through EDA tools. You'll own research projects that apply ML to these problems across the design flow, from problem definition through data, modeling, and evaluation, and turn successful results into capabilities in the ChipAgents platform. You'll work alongside other ML researchers, software engineers, and hardware experts.
Key ResponsibilitiesLead research projects that apply machine learning to power, performance, and area problems in chip design, from problem definition to production.
Build datasets and benchmarks from EDA tool flows across a range of designs and technologies.
Design, train, and evaluate ML models on hardware design data.
Form clear hypotheses, set strong baselines, and distinguish meaningful improvements from benchmark noise.
Work with engineering and product teams to bring research results into the ChipAgents platform.
Write well-architected, maintainable code that others can build on.
MS or PhD in Computer Science, Electrical or Computer Engineering, or a related field, or equivalent research experience in industry.
Strong ML fundamentals and hands-on experience designing, training, and debugging deep learning models in PyTorch or similar platforms.
Working knowledge of the digital design flow, from RTL through synthesis, place and route, and timing and power analysis.
Experience running and scripting EDA tools, commercial or open source.
Strong Python software engineering skills and a record of writing research code that others build on.
Ability to identify the crux of an ambiguous research problem, choose the experiments that matter, and explain results clearly to ML and hardware engineers.
Self-directed and ambitious, with strong ownership and good judgment about when work is ready to ship.
Publications at EDA venues such as DAC, ICCAD, MLCAD, or ISPD, or at ML venues such as NeurIPS, ICML, or ICLR.
Prior work applying ML to EDA or chip design problems.
Experience with ML on graphs or other structured data.
Industry experience in physical design, timing closure, or power analysis.
Experience with LLMs or agent systems.
Experience running large-scale training or data generation on compute clusters.
Your research ships to semiconductor companies and gets tested on their designs as well as public benchmarks.
Own research problems end to end, with software engineers who take your work into production and customer environments so you can stay focused on research.
Work alongside ML researchers and chip design veterans, and help set the research direction of a fast-growing team.
Publish and present your work at conferences where appropriate.
ChipAgents is an equal opportunity employer. We welcome applicants of all backgrounds.
What We Offer$150K/yr – $350K/yr base salary + 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.
Skills Required
- MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field, or equivalent industry research experience
- Strong machine learning fundamentals
- Hands-on experience designing, training, and debugging deep learning models using PyTorch or similar platforms
- Working knowledge of digital design flows from RTL through synthesis, place and route, timing, and power analysis
- Experience running and scripting commercial or open-source EDA tools
- Strong Python software engineering skills
- Record of writing research code that others can build upon
- Ability to define ambiguous research problems, select meaningful experiments, and communicate results clearly
- Self-directed approach, strong ownership, and sound judgment about production readiness
- Publications at EDA or machine learning conferences
- Prior experience applying machine learning to EDA or chip-design problems
- Experience with graph machine learning or other structured data
- Industry experience in physical design, timing closure, or power analysis
- Experience with LLMs or agent systems
- Experience running large-scale training or data generation on compute clusters
What We Do
ChipAgents is revolutionizing the chip design and verification process with agentic AI tools tailored for the semiconductor industry. Our flagship product, ChipAgents, leverages advanced AI agents to streamline and enhance the design, debugging, and verification of RTL (Register Transfer Level) code, accelerating time-to-market for chip developers. We are committed to empowering hardware design and verification engineers by providing cutting-edge solutions that improve efficiency, scalability, and accuracy in chip development. Based in Santa Barbara, CA, Alpha Design AI is at the forefront of AI innovation in electronic design automation (EDA).
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