Warp is the AI-driven U.S. chemistry CRO that turns AI-designed molecules into compounds drug discovery teams can test, in labs built for automation. Backed by Menlo Ventures.
About the role
Own the data agenda: Translate model failures and lab priorities into a collection and generation plan. Decide the right mix of open, licensed, synthetic, and real-world data. Prioritize coverage gaps, difficult cases, and highest-value expert involvement. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- A track record of improving model capabilities through better data, with hands-on ownership from identifying a gap to building the dataset and measuring results
- Practical experience with ML data development: synthetic generation, model rollouts, multimodal datasets, expert annotation, or real-world collection
- Strong understanding of data composition, sampling, demonstrations, rewards, and verifiers, and how they affect fine-tuning and RL
- Strong software engineering skills in Python, with experience building data pipelines, model-driven tools, and reproducible experiments
- Good judgment on data quality, provenance, licensing, leakage, and evaluation, and the ability to inspect and critically analyze examples
- Ability to set priorities across teams while staying hands-on. Use of AI tools and agents to multiply output and verify work. Collaborative mindset with researchers, chemists, and robotics engineers
More about this role
At Warp Sciences, our mission is to help the world discover new medicines faster—and build the capacity to do it here in America. We bring AI, robotics, and life sciences together in automated labs that design, run, and learn from experiments, with each experiment making the next one better. We’re not developing drugs of our own. We’re building the infrastructure for the people who do.
Warp is building autonomous laboratories that can run scientific experiments end-to-end. Our work combines robotics, automation, and advanced AI to enable breakthrough discoveries in chemistry and beyond. High-quality real-world data powers our systems, models, and robots.
We are looking for a senior, hands-on AI data builder to own what our models learn from. You’ll set the data strategy and build the systems to execute it across our chemistry foundation model, our lab perception stack, and our robot-learning system. You will determine what data matters, where to source or generate it, and how to turn it into measurable capability gains. Your scope will span open datasets, synthetic data, RL rollouts, expert feedback, teleoperation, and physical lab execution. You'll connect these sources through...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area