Machine Learning Engineer
Raydar
Machine Learning Engineer
Raydar
AI-powered recruiting agency for tech roles
Raydar · San Francisco, United States · Full-time · Posted 2026-11-07
Salary: USD 160,000–210,000
Workplace: on_site
About the company
Our client is a property technology company.
The role
Raydar is recruiting for this role on behalf of our client. Improve the accuracy of AI agents that analyze construction documents against regulatory requirements, working through model training, experiment design and evaluation. The role suits an engineer who can move quickly, test ideas rigorously and extend the product into new building types.
What you'll do
- Spend most of your time raising the accuracy of multimodal AI agents, including model post-training and automated research.
- Design experiments, build them out and analyze results on internal evaluation frameworks.
- Handle a range of supporting work such as light data engineering, tooling for the engineering team, and web application improvements.
- Develop new agents that extend the current product to commercial and multifamily housing nationwide.
- Speak with users on a weekly basis.
What we're looking for
- Works independently, moves at high speed and holds evaluation work to a rigorous standard.
- Either a strong software engineer transitioning into AI research, or an AI or machine learning engineer already working in the field.
- At least 3 years of relevant experience.
- Shared interest in housing supply and land-use reform.
- Willingness to work long weeks, roughly 55 hours, including some weekends.
Compensation and benefits
- Base salary: USD 160,000 to 210,000 per year
- 401(k) retirement plan with pre-tax and Roth contributions
- Health insurance, fully paid
- Employer health savings account contributions
- Commuter benefits
- Wellness benefit
- Meals provided at the office
Location and work model
- San Francisco, California, United States
- On-site
- Full-time
Powered by Workable
Raydar is an AI-powered talent acquisition firm that serves tech-focused organizations on a contingency basis, charging client companies only after a successful hire. It uses proprietary AI to identify a large pool of candidates and conducts a short 15-minute AI-driven interview (recorded and transcribed) before human recruiters review materials, provide interview prep, and assist with offers and negotiations. What sets it apart is the blend of automated sourcing and screening with hands-on human oversight and tailored client support. Its goal is to help organizations hire more efficiently by speeding up sourcing while maintaining thorough evaluation and negotiation assistance.
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