The role, as published
About the company
Our client is a fast-growing data company.
The role
Raydar is recruiting for this role on behalf of our client. Design and run data pipelines that turn raw technical and business materials into structured tasks and evaluations for training and testing machine learning systems. Work alongside research staff and subject-matter experts to set requirements, review samples, and build quality checks, then trace failures back to their causes to improve future datasets.
What you'll do
- Build scalable data pipelines that ingest large volumes of source material and convert it into training tasks and evaluations.
- Work with research teams to specify dataset requirements and review early samples before production scales up.
- Design quality checks and grading methods together with domain experts.
- Identify ambiguous, incorrect, or easily gamed tasks and correct them.
- Investigate review and delivery issues, fix root causes, and apply the findings to later datasets.
What we're looking for
- Proficient coder with a track record of shipping data workflows, automation, or software that uses AI.
- Genuinely technical, high-intelligence engineer with strong first-principles problem solving.
- Able to translate an open-ended question from researchers into a workable engineering plan and assess how well it performs.
- Detail-oriented, happy to go through single records by hand and hunt down mismatches.
- Able to explain ideas clearly to scientists and domain specialists before the specs are settled.
- 1 to 4 years of relevant experience.
Bonus points
- Background in data delivery or quantitative work.
- Familiarity with benchmarking models, generating artificial training data, or autonomous software agents is a plus.
Benefits
- Health, dental and vision coverage
Location and work model
- San Francisco, CA, United States
- On-site
- Full-time
Compensation, as the posting describes it
- Base salary: $200,000 to 400,000
- Equity