The role
- COMP
- $180K - $250K
- EQUITY
- 0.3-0.7%
- LOCATION
- San Francisco · South Bay Area
- WORKPLACE
- On-site
- EXPERIENCE
- 4 - 7 years
- VISA
- None, Visa transfers
- STACK
- Python, Django, AWS, GCP, Docker
- INDUSTRY
- AI, Hardware, Software Development
/roles — ROLE_207
Software Developer Engineer
Accelerator-backed startup training AI models for mechanical design and automating tedious CAD work
The company
Early-stage startup building AI-driven CAD tools that automate repetitive design work so hardware engineers can move from concept to final design faster.
- STAGE
- Series A-stage
- FUNDING
- $9M raised
- TEAM
- founding team of <10
- FOUNDED
- 2024
- BACKING
- VC-backed
JD — the work
About the role
The team is tiny, just a handful of people, and is building CAD software with AI at its core, including AI models aimed at mechanical engineering. Having settled its core technical questions, the startup is now scaling fast and expects to roughly double in size soon. The founding team came from the early days of a high-profile startup that was later acquired, and they want to build that kind of company again. You would own core systems end to end, including the production ML behind the product.
What you'll do
- Take core systems from an ambiguous problem statement to a shipped, well-maintained product
- Work with the founders to turn loose goals into technical plans, then drive them to launch
- Lead how the ML systems behind the AI-powered CAD product are designed and put into production
- Raise engineering standards through code review, testing practices, and architectural direction
- Debug everything from routine defects to deep performance, reliability, and scaling issues
- Strengthen CI/CD, testing, and observability as the product and team grow, and help shape the culture
What they're looking for
- At least 3 to 4 years writing and shipping software used in production
- Strong Python and a record of building scalable backend services with tools like Django, Flask, and SQL
- Practical experience putting ML models into production
- Proven ownership of whole systems and good judgment on architecture tradeoffs with minimal guidance
- Solid CS fundamentals, clear communication, and comfort with ambiguity
Nice to have
- Background in CAD, geometry, or computational geometry
- C# or .NET, since some add-ins are written in C#
- Packaging and shipping signed native desktop apps for Windows and macOS
- Large-scale AWS and DevOps depth, or early-stage 0-to-1 product experience