Engineer, New Grad

Job Description

Job Description

San Francisco, CA · On-site · Full-time
Compensation: $150,000 – $220,000 base (total compensation up to approximately $300,000) + competitive equity

About the Company

Our client is a Series A spatial intelligence company building foundation models for the next generation of engineering design. Today's foundation models have no real spatial understanding, which keeps them out of the work that actually matters in engineering and manufacturing. Our client trains large models without that limitation, capable of reasoning about and designing physical systems. The team is small and technically dense, roughly a dozen people today and growing, with founders and early hires drawn from top industrial research labs and leading CS programs.

The Role

This is a deliberately broad engineering role for someone early in their career. You would work across machine learning, geometry, graphics, and AI, and the team is hiring for raw ability rather than domain background. No CAD or manufacturing experience is expected. What they want is real strength in one area and genuine curiosity about the rest, and a generalist who finishes hard things nobody assigned them.

What you'll be doing

• Build and maintain geometry and data pipelines: parsing CAD, converting formats, extracting features, and verifying that what comes out matches what went in.
• Write the evaluation harnesses and tooling that tell the team whether a model actually improved.
• Support training and experiment runs by instrumenting them, debugging failures, and turning results into something readable at a glance.
• Build internal tools that remove friction for the rest of the team.
• Own well-scoped pieces of larger research and engineering efforts, and grow your scope as you earn it.

Tech stack: Python, C/C++, PyTorch, CUDA, data pipelines, computer graphics, computational geometry, Linux, Git

Requirements

• Up to roughly two years of software engineering experience, counting internships and research.
• Hands-on work in at least one of the following: training machine learning models, building data pipelines, or building internal tooling.
• Internship or research experience somewhere with a genuinely high hiring bar, whether that's a leading aerospace, automotive, autonomy, or AI company, or an academic research lab affiliation.
• A bachelor's or master's degree in computer science, engineering, mathematics, or physics from a strong, competitive program.
• Strong practical coding ability in Python, C, or C++.
• Comfortable working as a generalist first and specializing later, once you've found where you're strongest.
• Able to work on-site in San Francisco five days a week.

Nice to Haves

• Some exposure to one of these adjacent areas: CAD, robotics, perception, or graphics and game design. Coursework or personal projects are enough here, and depth is not expected.

Why Join

• You would be working directly on the core model rather than on tooling around a finished product, at a stage where the technical direction is still being set.
• Wide surface area across ML, geometry, graphics, pipelines, and internal tools, so you can find out what you're best at instead of being slotted into a lane on day one.
• A small team where senior people are available whenever you ask, but you are the one steering your own work.
• Compensation at the top of the new grad market, plus meaningful equity.
• Relocation support is available, and the team is open to both visa transfers and new sponsorships.

Details

• Location: San Francisco, CA
• Work policy: 5 days per week in-office; relocation support offered
• Compensation: $150,000 – $220,000 base + competitive equity
• Visa sponsorship: Open to transfers (OPT, H-1B) and to new sponsorships (new H-1B, TN, O-1)
• Employment type: Full-time