Machine Learning Scientist, RL – Autonomous Discovery

🕒 July 1

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Terray Therapeutics

WebsiteLinkedInAll Job Openings

11 - 50 employees

🧬 Biotechnology

🤖 Artificial Intelligence

💊 Pharmaceuticals

💰 $60M Series A on 2022-02

Biotechnology • Artificial Intelligence • Pharmaceuticals

Terray Therapeutics is a company revolutionizing small molecule drug discovery through a platform that integrates wet lab science with artificial intelligence. By focusing on high-quality, large-scale data, Terray unlocks generative AI for solving complex therapeutic challenges. The company's platform accelerates the drug discovery process with an experimental dataset containing billions of target-ligand binding measurements, supported by deep learning regression models. Terray Therapeutics prioritizes immunology internally but also collaborates with pharmaceutical and biotech organizations to tackle a variety of tough targets and therapeutic areas.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• 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 • above-market life insurance • disability coverage • meaningful support across every stage of life