Founding Machine Learning / Research Engineer

This role is hybrid, with three days a week in the office in San Francisco.

We are helping an early stage, venture backed company in San Francisco hire a founding machine learning and research engineer. The company builds AI systems that recreate real hardware design work, including CAD and electrical CAD tasks, so models and agents can practice that work, be evaluated on it, and get better at it. You would be one of the first machine learning hires and would help set how this research becomes production software.

The focus of this seat is reinforcement learning environments, evaluations, and graders for agentic CAD and electrical CAD systems. It is not centered on RLHF, foundation model architecture, or retrieval work. The company is hiring for one seat.

What you will do

• Design and improve reinforcement learning environments that reflect real CAD and electrical CAD workflows, including the constraints an engineer would face in a real design review.

• Build evaluations and graders that measure whether an agent completed hardware design work well, and keep those signals honest as the environments get harder.

• Take machine learning from research into production, including evaluations, grading, data pipelines, and the infrastructure the models run on.

• Sit with electrical and mechanical engineers, learn how they judge a design, and turn that judgment into machine learning problems and training signal.

• Advance how AI handles hardware engineering work that is visual, spatial, and tied to physical parts, not only text.

• Own your research end to end: the question, the experiment, the result, and the path into the product.

What you need

• 3 or more years as a machine learning engineer, including production work and multimodal work.

• Experience with reinforcement learning environments, either building and shipping them or using them for post-training.

• A hardware connection: machine learning at a hardtech company, close work with electrical or mechanical engineers, or a degree in electrical or mechanical engineering.

• Knowledge of CAD, electrical CAD, 3D vision, or other hardware-adjacent machine learning.

• Foundational machine learning experience, including models you have built and trained, not only applications on top of someone else's models.

• Senior ownership of your work. You can set the research plan and ship it without close supervision.

• US citizenship or permanent residency. This role cannot support visa sponsorship.

• You can be in the San Francisco office three days a week.

Nice to have

• Experience translating domain expert judgment into machine learning problems.

• Experience with generative CAD tools.

What this search is not

• This search is not for people who only work on application-layer AI without machine learning depth.

• This search is not for histories with many short stints.

• This search is not centered on RLHF, reward modeling, foundation model architecture, retrieval systems, or noisy-label cleaning.

Location

• Hybrid in San Francisco, California, three days a week in the office.

• Full time, direct hire role. Equity is part of the offer.

How to apply

Apply through this posting, or book a time with our team at calendly.com/risehire/30min. We accept applications on an ongoing basis until the role is filled.

Rise Talent Advisors is an equal opportunity employer. We welcome people of all backgrounds.