Data Quality Engineer: Build Reliable AI Data Pipelines

reflectionai; San Francisco, New York (CA, NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Top-tier compensation

Stock options

Health & wellness

Meals provided

Parental leave

Unlimited vacation (US)

Visa sponsorship

Team events

Job summary

Reflectionai in San Francisco is seeking a Data Quality Engineer to join the Data Team and ensure high-quality data for post‑training and evaluation. You will shape how data quality affects model capabilities in agentic tool use, long‑horizon reasoning, and safety alignment.

You will work with researchers and engineers to translate quality requirements into measurable signals, design scalable QA methods, and build pipelines that reliably deliver data for training and assessment.

Qualifications

• Strong engineering fundamentals in data pipelines and QA systems.
• Analytical mindset with ability to spot data quality issues.
• Experience with automated quality checks and LLM‑as‑a‑Judge.

Responsibilities

• Own upstream data quality for post‑training and evaluation.
• Translate requirements into measurable quality signals for data vendors.
• Design, validate, and scale automated QA methods for large campaigns.
• Build reusable QA pipelines delivering high‑quality data for training and evaluation.
• Monitor data quality over time and iterate on standards and criteria.

Skills

Python proficiency

ML/LLM workflows

Data pipelines

Automated evaluation

Communication skills

Job description

Reflectionai in San Francisco is seeking a Data Quality Engineer to join the Data Team and ensure high-quality data for post‑training and evaluation. You will shape how data quality affects model capabilities in agentic tool use, long‑horizon reasoning, and safety alignment.

You will work with researchers and engineers to translate quality requirements into measurable signals, design scalable QA methods, and build pipelines that reliably deliver data for training and assessment.