# Engineer New Grad at Raydar

- Company: Raydar
- Location: San Francisco, CA
- Type: Full-time · Entry
- Posted: 2026-10-29
- Apply: https://apply.workable.com/raydar/j/99A94AA059/apply
- Page: https://newgrad.ai/jobs/engineer-new-grad-53c08731

## Summary by newgrad.ai

What you'll do:

- Develop geometry and data pipelines for CAD parsing and feature extraction.
- Create evaluation tools to measure and improve model performance.
- Assist with machine learning training, debugging, and system instrumentation.
- Build internal software to streamline engineering and research workflows.

What they're looking for:

- Bachelor’s or master’s degree in a technical or quantitative field.
- Zero to two years of experience, including internships or research.
- Proficiency in Python, C, or C++.
- Ability to work on-site in San Francisco five days weekly.

Pay and perks:

- Base salary between $150K and $220K.
- Total compensation approximately $300K including bonus.
- Visa sponsorship available.

## Posting

### About the company

Our client is a venture-backed spatial intelligence company building foundation models for physical engineering design. Its first model is a generative foundation model for structured 3D parametric CAD, and the team is now developing the next generation of its system. Founded in 2022 and backed with $27M in funding, the company has grown from six people at its last financing to a highly technical team of 12.

### The role and why it matters

This is a broad new-graduate engineering role for someone with strong fundamentals and the curiosity to work across machine learning, geometry, graphics, data systems, evaluation, and internal tooling. You will begin with well-scoped projects, learn the full system, and take on more ownership as you demonstrate strength. No CAD or manufacturing background is required.

### What you'll do

- Build and maintain geometry and data pipelines that parse CAD, convert formats, extract features, and verify output quality.
- Write evaluation harnesses and tooling that help the team determine whether model performance has improved.
- Support machine learning training and experiment runs, instrument systems, debug failures, and present results clearly.
- Build internal tools that remove friction for researchers and engineers.
- Work across the stack and develop depth in the areas where you have the greatest impact.
- Own challenging technical problems in close collaboration with a small, experienced team.

### What we're looking for

- Zero to two years of software engineering experience, including internships or research.
- A bachelor's or master's degree in computer science, engineering, mathematics, physics, or a closely related field from a rigorous program.
- Hands-on experience with machine learning training, data pipelines, internal tooling, or adjacent technical work.
- Strong programming ability in Python and/or C or C++.
- Evidence of high performance through internships, research, ambitious technical projects, or work in a demanding engineering environment.
- A generalist mindset, intellectual curiosity, and willingness to begin broadly before specializing.
- A track record of finishing difficult work and taking initiative without waiting for detailed instructions.

### Bonus points

- Exposure to CAD, computational geometry, robotics, perception, graphics, game development, or related coursework and projects.
- Experience building evaluation systems or supporting model training infrastructure.
- Research or internship experience at a high-bar technology company or laboratory.

### Compensation and benefits

- $150K-$220K base salary.
- Total compensation around $300K, including bonus.
- Competitive equity and benefits.
- Visa sponsorship and transfers may be available, including F-1 OPT, H-1B transfers, new H-1B sponsorship, and TN visas.

### Location and work model

This is a full-time role based in San Francisco, California. The team works together in the office five days per week, and candidates must be able to work on-site or relocate before starting.

From Raydar's public posting, laid out for reading by newgrad.ai with the wording unchanged. Check the original before you apply.

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More new-grad and intern roles: https://newgrad.ai/llms.txt