RL Data Quality Lead: Scalable Training & Evaluation

Clera; San Francisco (CA); On-site; USD 150,000 - 250,000; Full time

Benefits offered by this job

Equity participation

Visa sponsorship

Relocation assistance

Job summary

Clera in San Francisco, CA is hiring a Lead Research Engineer, Data Quality to own strategy and systems for measuring, improving, and scaling training data for frontier agents in RL environments. This high-impact, hands-on leadership role shapes both technical direction and research culture.

You will lead a data quality team, build QC pipelines, validate synthetic data at scale, and collaborate with researchers and data vendors to deliver reliable, diverse datasets used to train next-generation

Qualifications

• 5+ years of engineering or research experience.
• Proven track record leading technical teams on ambiguous projects.
• Advanced proficiency in Python, Docker, and Linux environments.
• Hands-on experience building QC systems, evals, benchmarks, or validation workflows.
• Deep intuition for data quality in training data.
• Strong written communication for researchers and engineers.
• Experience with startup environments and independent work.

Responsibilities

• Lead the data quality team in building evaluation systems for RL tasks.
• Define data quality strategy, QC systems, standards, and experiments.
• Develop scalable validation for synthetic data and trajectory auditing.
• Collaborate with researchers, domain experts, and data vendors to diagnose quality issues.
• Translate research insights into production tools, dashboards, and validation pipelines.
• Mentor engineers, upholding rigor, clarity, and execution speed.

Skills

Data quality

Leadership

Python

Docker

Linux

Communication

Independent work

Attention to detail

Tools

QC systems

Benchmarks

Synthetic data pipelines

Validation workflows

Model evaluation infra

Job description

Clera in San Francisco, CA is hiring a Lead Research Engineer, Data Quality to own strategy and systems for measuring, improving, and scaling training data for frontier agents in RL environments. This high-impact, hands-on leadership role shapes both technical direction and research culture.

You will lead a data quality team, build QC pipelines, validate synthetic data at scale, and collaborate with researchers and data vendors to deliver reliable, diverse datasets used to train next-generation