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Warp Sciences

AI-driven chemistry CRO for lead optimization

Member of Technical Staff - Post Training

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSouth San Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • Experience working at the frontier of model capabilities, with meaningful personal ownership of post-training results.
  • Ability to achieve state-of-the-art results and substantiate them with rigorous evaluation against strong baselines.
  • Deep practical experience with reinforcement learning, including reward design, rollout systems, training stability, and diagnosing failure modes.
  • An evaluation-led approach: define success before optimizing and scrutinize whether measured gains reflect the intended behavior.
  • Strong data intuition, with experience identifying, creating, and selecting data that produces measurable improvements.
  • Strong engineering skills and experience building reliable training and experimentation systems.
  • A track record of shipping model improvements into real products and learning from deployment.
  • An outcome-driven approach that follows evidence, moves quickly, and takes responsibility for whether work improves the product.

Responsibilities

  • Own the post-training loop from identifying a capability gap through evaluation, data development, training, deployment, and production feedback.
  • Build evaluations grounded in product needs, with clear baselines and held-out tests that distinguish real progress from benchmark overfitting.
  • Build experimentation systems that enable fast, reproducible hill climbing and make results easy to compare and diagnose.
  • Develop and improve reinforcement learning training methods, reward signals, rollout generation, and supporting infrastructure.
  • Curate, generate, and refine training data based on model failures, evaluation results, and product feedback.
  • Improve model behavior across Warp’s robotics and foundation-model stack, working closely with robotics, infrastructure, and product teams.
  • Validate gains through ablations, robust comparisons, and testing beyond the training distribution.
  • Ship improvements, measure their impact in production, and use what is learned to drive the next iteration.
  • Establish a credible baseline, identify important failures, and build a repeatable loop that improves them; ensure results hold up under rigorous evaluation and translate into better product behavior, with each deployment informing the next iteration.

Desired Qualifications

  • Experience with robotics, embodied artificial intelligence, or learning from interaction.
  • Experience post-training multimodal, perception, or action-generating models.
  • Experience balancing model quality with latency, compute, and deployment constraints across local and cloud environments.

About the Company

Warp Sciences

AI-driven chemistry CRO for lead optimization

Warp Sciences is a US-based chemistry contract research organization (CRO) that combines chemists, artificial intelligence, and robotics to create and test molecules for biotech and pharmaceutical companies. It does not own a drug pipeline; customers decide which molecules to pursue and retain control of their drug programs. Its initial service is lead-optimization analog synthesis, where variations of promising molecules are produced and compared by research teams to select drug candidates. Chemists design experiments while the lab becomes increasingly automated; data from experiments trains AI models that help run the lab more efficiently. Customers pay per compound delivered. The company aims to bring discovery chemistry work back to the United States and was founded by Kevin Weil, DJ Patil, Sol Reisberg, and Mano Paluri, with backing from investors like Lightspeed and Mayfield.

Company size
1-10
Company stage
Early VC
Total funding
$215M
Headquarters
South San Francisco, CA
Founded
2026

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