Member of Technical Staff, AI Engineering

What you'll do

• Design and build systems for synthetic data generation and data anonymization/PII removal.
• Translate research, partner, and compliance needs into experiments, evaluations, production implementations, and reusable platforms.
• Improve data pipelines, benchmarks, and quality-control systems through rapid iteration and collaboration with researchers, experts, and compliance stakeholders.

What they ask for

• 2–10 years of recent demonstrated experience in one or more of synthetic/LLM-generated data, post-training and model evaluation, privacy engineering, or data anonymization/de-identification at scale.
• Strong Python skills and ability to build clean, efficient, scalable software for large, messy datasets.
• Hands-on individual-contributor track record; not a team-lead or engineering-management role.
• Experience designing systems and sound judgment about data quality, risk, utility, and system tradeoffs.

Nice to have

• Large-scale synthetic/LLM data pipelines, de-identification systems, or LLM/agent evaluation and data-quality frameworks.
• Relevant research, regulated or sensitive-data experience, technical leadership, or productizing research into reusable platforms.

Pay

$200K – $350K (base salary)

Tools

Python

AI focus

Build training-data generation and processing systems, including synthetic and LLM-generated data, evaluation frameworks, and privacy-preserving de-identification for frontier models.