Research Engineer, ML for EDA

ChipAgents•San Jose, CA

1d•$150,000 - $350,000

About The Position

ChipAgents is hiring Research Engineers to apply machine learning to electronic design automation (EDA). The role focuses on power, performance, and area challenges in chip design, applying ML across the design flow. Research Engineers own projects from problem definition through data collection, modeling, and evaluation, and help turn successful results into capabilities in the ChipAgents platform. They work alongside ML researchers, software engineers, and hardware experts. The role offers the opportunity to conduct research that is tested on semiconductor companies’ designs and public benchmarks, own research problems end to end with engineering support for productionization, help shape the research direction of a fast-growing team, and publish and present work at conferences where appropriate. The position includes a base salary of $150,000–$350,000 per year plus equity, with above-scale compensation open to discussion for exceptional candidates. Benefits include unlimited PTO and medical, vision, dental, and 401(k) benefits. ChipAgents also describes engineering-centric offices with free parking, a private gym, and free lunch, drinks, and snacks.

Requirements

MS or PhD in Computer Science, Electrical or Computer Engineering, or a related field, or equivalent research experience in industry.
Strong machine-learning 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 commercial or open-source EDA tools.
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 relevant experiments, 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.

Nice To Haves

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.

Responsibilities

Lead machine-learning research projects addressing 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 machine-learning models on hardware-design data.
Form clear hypotheses, establish 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.