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Terray Therapeutics VERIFIED EMPLOYER

Machine Learning Scientist, RL & Autonomous Discovery.

Remote Data Science & ML Full-Time

Machine Learning Scientist, RL & Autonomous Discovery: our view in 3 lines...

  • The Role:An ML scientist role focused on reinforcement learning to invent and scale systems for autonomous discovery of novel chemical matter in a scientific/biotech context.
  • The Person:Design and develop RL frameworks, build synthetic data engines and inference infrastructure for large-scale training, and maintain evaluations of learned policies using proprietary experimental datasets.
  • Requirements:Required skills include reinforcement learning, bayesian and black-box optimization, experience with distributed training and inference frameworks, and substantial publications or proven research contributions.

About the role

Position Summary:  Terray Therapeutics is seeking an ML Scientist with a background in reinforcement learning. In this role, you will work to invent and scale cutting-edge systems that discover novel chemical matter and impact real programs. Terray’s machine learning team affords a broad creative scope, and the opportunity to directly affect real programs.

The key responsibilities of this role are:

  • Contribute to RL frameworks that drive the design-make-test-analyze (DMTA) cycles that power our EMMI platform, which coordinates a closed-loop between a highly automated lab and our reward models.
  • Develop synthetic data engines and the inference infrastructure needed to simulate environments for large-scale training.
  • Maintain rigorous evaluations to continually monitor the performance of learned policies, using large proprietary datasets collected from internal programs.

Experience and Qualifications: Part of Terray's success is nurtured by a hands-on work environment where everyone is accountable, vested in a vision of excellence, and actively taking part in the success of the business. Terray supports a positive work environment where employees can feel engaged, recognized, and empowered to be creative.

Required Qualifications: 

  • Strong experience in machine learning, with interest in techniques for sequential decision-making: bayesian and black-box optimization, reinforcement learning.
  • Experience with distributed training and inference frameworks.
  • Substantial publications (NeurIPS/ICML/AISTATS) or proven record of research contributions.
  • Ability to quickly switch between robust engineering and exploration of conceptual insights: the implementation details of training on asynchronous rollouts, and understanding why policy divergence leads to instabilities.
  • Experience with the challenges of complex real-world systems and scientific environments, such as expensive queries and experimental noise.
  • Appreciation for elegant ideas and what works in practice.

Only applicants with github, proof of relevant work, or a one-page writeup of experience applying autonomous discovery to a scientific problem that is verifiable will be considered.

Compensation Details: $XXX–$YYY annually, depending on experience. Terray’s salary ranges are designed to be competitive and are benchmarked against market base salary plus bonus within our industry and market. We align pay to role scope, skill level, and impact.

We invest heavily in benefits because taking care of our people matters. Our programs are benchmarked at the top of the Southern California market and designed to provide meaningful support across every stage of life. Benefits include participation in the Company’s stock option plan, a 3% retirement safe harbor contribution, fully paid health, dental, vision insurance for our employees, spouse, partner and families as well as above-market life insurance, disability coverage, and much more to explore during the offer process.

Published July 1, 2026
Location United States of America
Category Data Science & ML  
Job Type Full-Time