Machine Learning Engineer

The role

Raydar is recruiting for this role on behalf of our client. Build and evaluate machine learning systems for an interactive consumer product, spanning research and production. You will take features from early scoping through measurement and release, choosing between novel models and standard software engineering practice to fit each problem.

What you'll do

• Help set the goals and measures of impact for AI features in the product.
• Own AI systems end to end, from spotting opportunities to building evaluation tooling and shipping production improvements.
• Partner with learning specialists and product engineers to build infrastructure that measures quality, engagement, safety, latency and behavior.
• Design and refine the orchestration layer that decides an interactive assistant's next step and when it should step in.
• Build user modeling and adaptation systems that tailor decisions to each user's progress, gaps and engagement patterns.
• Create feedback loops that improve product quality through usage data, evaluation and experiments.

What we're looking for

• Hands-on time building and running systems that grade model output for AI or language-model products.
• Background either in delivering AI-powered functionality to users or in machine learning research.
• Familiarity with serving language models with minimal response delay at high volume.
• A prior engineering role at a company that moves quickly and is built around AI.
• An undergraduate degree in computer science, electrical engineering and computer science, or an equivalent engineering subject.

Bonus points

• Experience building AI systems that end users interact with directly in consumer settings.
• Exposure to tuning large language models, particularly for speech tasks.
• Background at consumer-facing AI firms or companies that make learning software.

Compensation and benefits

• Base salary: $165K - $230K
• Equity
• Paid time off and holidays
• Medical, dental and vision coverage

Location and work model

• San Francisco, CA, United States
• Hybrid, 3 in-office days per week
• Full-time