
Machine Learning Scientist, RL – Autonomous Discovery
Posted Jul 1

Posted Jul 1
This is a fully remote position, open to applicants in United States.
• Play a key role in developing RL frameworks that facilitate the design-make-test-analyze (DMTA) cycles for our EMMI platform, which integrates a highly automated lab with our reward models.
• Create synthetic data engines and the necessary inference infrastructure to replicate environments for large-scale training purposes.
• Conduct thorough evaluations to consistently assess the performance of learned policies, utilizing extensive proprietary datasets gathered from internal initiatives.
• Extensive experience in machine learning, particularly in techniques related to sequential decision-making, including Bayesian and black-box optimization, as well as reinforcement learning.
• Familiarity with distributed training and inference frameworks.
• A significant publication record (NeurIPS/ICML/AISTATS) or a demonstrated history of impactful research contributions.
• Capability to seamlessly transition between robust engineering practices and the exploration of conceptual insights, including the implementation intricacies of training on asynchronous rollouts and understanding the causes of policy divergence leading to instabilities.
• Experience addressing the complexities of intricate real-world systems and scientific environments, such as costly queries and experimental noise.
• A keen appreciation for elegant ideas and practical effectiveness.
• Only candidates with a GitHub portfolio, evidence of relevant work, or a one-page summary detailing their experience in applying autonomous discovery to a scientific challenge that is verifiable will be considered.
• Participation in the Company’s stock option plan.
• A 3% retirement safe harbor contribution.
• Comprehensive health, dental, and vision insurance for employees, spouses, partners, and families, fully covered.
• Above-market life insurance coverage.
• Disability insurance.
• Meaningful support throughout all stages of life.
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