The role
- COMP
- $200K - $300K
- EQUITY
- Competitive equity
- LOCATION
- San Francisco
- WORKPLACE
- On-site
- EXPERIENCE
- 6 - 10 years
- VISA
- None
- STACK
- Python, C/C++
- INDUSTRY
- AI, Manufacturing, Robotics
/roles — ROLE_294
Product Manager / GTM
Early-stage lab training models that generate and reason about 3D CAD for engineering teams
The company
AI lab training large foundation models with a native grasp of 3D geometry, aimed at automating engineering design and CAD work for physical products.
- STAGE
- early-stage
- FOUNDED
- 2022
JD — the work
About the role
This is a hybrid product and go-to-market role for someone who knows CAD deeply and can write code. You would turn the company's model outputs into polished demos, prototypes and experiences that engineers and designers value right away, work with design partners across product design, mechanical engineering and manufacturing, and bring a practitioner's judgment to research priorities and the roadmap. It sits where early customers, the research team and the product meet.
What you'll do
- Create demos and prototypes for each model release that make raw outputs immediately useful to engineers
- Judge model output by professional CAD standards and stress-test new features against real engineering workflows
- Put together custom demos and sample datasets aimed at particular prospects, industries and applications
- Write scripts and internal tooling that make working with CAD files and model results faster for everyone
- Relay what users need to researchers and engineers, filtered through a clear sense of what is technically feasible
- Inform roadmap priorities using hands-on domain knowledge of which capabilities to build first
- Present the product to prospective customers and technically demanding CAD users
What they're looking for
- 6 to 10 years of experience, with CAD domain expertise at the core
- Practitioner-level CAD knowledge and a feel for how engineers actually work day to day
- Comfortable coding your way through difficult, practical problems
- Firsthand familiarity with the bottlenecks engineers face in product design, mechanical engineering or manufacturing
- Ability to weigh user requests against what the technology can realistically do