Research Engineer: RL Data QA & Tooling

talentpluto; San Francisco (CA); On-site; USD 120,000 - 140,000; Full time

Benefits offered by this job

Medical/dental/vision coverage

Meals

401(k)

Commuter benefits

Wellness perk

Job summary

talentpluto is seeking a Research Engineer to enhance the quality assurance (QA) systems supporting training data for reinforcement learning. This position demands close collaboration with stakeholders to guarantee reliability and consistency in datasets.

Key responsibilities include defining quality standards, building auditing workflows, and integrating learnings into processes. Ideal candidates will have strong Python skills, experience with Docker, and a proven ability to operate independently in fast-paced settings. Competitive compensation and benefits are offered.

Qualifications

• Proficiency with Python and experience working in Linux environments.
• Experience with Docker and reproducible development/deployment workflows.
• Experience working with large-scale datasets (validation, transformation, or analysis).
• Strong problem-solving skills and evidence of rapid learning in technical environments.
• Ability to operate independently and deliver results in an early-stage, fast-moving setting.

Responsibilities

• Define and enforce quality standards for training datasets.
• Build tooling and workflows to audit supplier-generated datasets.
• Evaluate and implement human-in-the-loop review workflows.
• Partner with external data suppliers to debug quality issues.
• Integrate QA learnings into internal tools and supplier portals.

Skills

Proficiency with Python

Experience with Docker

Strong problem-solving skills

Clear written and verbal communication

Job description

talentpluto is seeking a Research Engineer to enhance the quality assurance (QA) systems supporting training data for reinforcement learning. This position demands close collaboration with stakeholders to guarantee reliability and consistency in datasets.

Key responsibilities include defining quality standards, building auditing workflows, and integrating learnings into processes. Ideal candidates will have strong Python skills, experience with Docker, and a proven ability to operate independently in fast-paced settings. Competitive compensation and benefits are offered.