Post-Training AI Systems Engineer (RL/Robotics)

Warp Sciences; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Warp Sciences is building scientific infrastructure in the United States to accelerate discovery of new medicines. We bring AI, robotics, and life sciences together in increasingly automated labs designed to run experiments, learn from the results, and improve with every cycle.

The post-training research engineer or scientist will own the end-to-end post-training loop, improving RL capabilities, evaluation systems, and deployment into real products across Warp's robotics and foundation-model

Qualifications

• Track record of meaningful results with systems that support rapid experimentation.
• Shipped improvements into real products and learned from deployment.
• Strong hands-on experience with reinforcement learning.
• Eval-led approach: define success before optimization and verify gains.
• Data-driven approach: identify, create, and select data that yields measurable improvements.
• Helpful: robotics, embodied AI, or learning from interaction.
• Helpful: post-training multimodal, perception, or action-generating models.
• Helpful: balancing model quality with latency, compute, and deployment constraints.

Responsibilities

• Own the post-training loop from capability gap through evaluation, data development, training, deployment, and production feedback.
• Build evals grounded in product needs with clear baselines and held-out tests.
• Create experimentation systems for fast, reproducible hill climbing and easy result comparison.
• Develop and improve RL 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 in collaboration with robotics, infrastructure, and product teams.
• Validate gains through ablations, robust comparisons, and testing beyond the training distribution.
• Ship improvements, measure production impact, and inform next iteration.

Skills

Reinforcement learning

Evaluation design

Experimentation systems

Post-training research

Product-focused ownership

Job description

Warp Sciences is building scientific infrastructure in the United States to accelerate discovery of new medicines. We bring AI, robotics, and life sciences together in increasingly automated labs designed to run experiments, learn from the results, and improve with every cycle.

The post-training research engineer or scientist will own the end-to-end post-training loop, improving RL capabilities, evaluation systems, and deployment into real products across Warp's robotics and foundation-model