Member of Technical Staff - AI Training Data

What you'll do

• Set data priorities and build pipelines for external, synthetic, RL, expert-feedback, teleoperation, and physical-lab data.
• Develop curation, ingestion, storage, lineage, and dataset-delivery workflows; assess data quality, provenance, licensing, and relevance.
• Partner with research and engineering teams to measure data-driven capability gains through evaluations, fine-tuning, and RL experiments.

What they ask for

• Track record of improving model capabilities through hands-on data development and measured results.
• Practical experience with ML data development, such as synthetic generation, model rollouts, multimodal datasets, expert annotation, or real-world collection.
• Strong understanding of data composition, sampling, demonstrations, rewards, and verifiers and their effects on fine-tuning and RL.
• Strong Python software engineering skills, including data pipelines, model-driven tools, and reproducible experiments.

Nice to have

• Experience with chemistry or scientific data, vision-language models, video understanding, or embodied AI.
• Background in teleoperation, demonstrations, simulation, active learning, human-feedback workflows, or RL-based data generation.

Tools

Python, Vault

AI focus

Build and improve data systems and workflows that train and evaluate chemistry foundation models, lab perception systems, and robot-learning systems; includes synthetic data, model rollouts, RL, and AI-assisted curation.