Machine Learning Scientist/Senior Machine Learning Scientist - Synthesis Planning and Optimization, AI for Drug Discovery

Job Description

• Build machine-learning methods for synthesis-aware molecular design, retrosynthesis, molecular generation, and search across synthesizable chemical spaces.
• Develop scalable active-learning pipelines and batch synthesis-planning algorithms that connect with automated and high-throughput synthesis platforms.
• Integrate proprietary reaction and biochemical data to support hit finding and molecular optimization.
• Requires a PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering, physics, statistics, or a related quantitative field; up to 2 years of industry research experience for Scientist or 2+ years for Senior Scientist.
• Full-time role based primarily in San Francisco, CA, with New York City, NY also referenced; relocation benefits are not available.