Machine Learning Engineer
Raydar
Machine Learning Engineer
Raydar
AI-powered recruiting agency for tech roles
Raydar · San Francisco, United States · Full-time · Posted 2026-10-22
Salary: USD 200,000–350,000
Workplace: on_site
About the company
Our client is an artificial intelligence company.
The role
Raydar is recruiting for this role on behalf of our client. Own the model development lifecycle for a software product, from experimentation through evaluation and deployment. Work as an individual contributor on a small team, creating the measurement tools and datasets that guide model quality.
What you'll do
- Train, adapt and assess generative models that power a software product.
- Design evaluation suites and iterative feedback processes to compare image and video models.
- Convert user activity and expert human judgment into curated datasets for training and testing.
- Develop compact in-house models aimed at better speed and quality.
- Determine which examples to gather, annotate and refine so that model output keeps getting better.
What we're looking for
- 3 to 6 years of experience as a machine learning engineer.
- Practical background with current generative approaches for images and video, such as diffusion.
- Proven record of taking models from training through to production use.
- Sound judgment about dataset design, annotation and curation.
- An implementer's mindset: you build and deliver working systems rather than only advising or publishing.
- Experience on a respected computer vision or generative media team.
- Comfort being the main owner of modeling work in a small, fast-moving environment.
Compensation and benefits
- Base salary: USD 200,000 to 350,000 per year
- Equity
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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