Machine Learning Research Scientist - Chemistry & Robotics

onepot; South San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Lunches and dinners in office

Job summary

onepot is automating chemistry and building a self-improvement loop by combining AI and robotics. We are seeking a machine learning researcher to train the next generation of chemistry models and enable synthesis of previously inaccessible molecules.

You will work across the full modeling stack with lab staff on data acquisition, train diverse models, and deploy them into experimental workflows. Strong ML fundamentals and curiosity about chemistry are essential, with ownership in a startup

Qualifications

• No formal education is required; ideal candidates have a deeply quantitative background or experience training ML models.
• Strong fundamentals in machine learning with an empirical/experimental focus.
• Ability to move quickly, make decisions with incomplete information, and solve difficult problems.
• Experience in startup or research environments with ownership and limited resources is relevant.

Responsibilities

• Train the next generation of chemistry models and enable synthesis of previously inaccessible molecules.
• Collaborate with lab staff on data acquisition and train models of varying shapes and sizes.
• Deploy models directly into experimental workflows and maintain ML training infrastructure and data pipelines.
• Develop abstractions for training diverse models, including parallelism strategies and quantization.
• Aim to train models with superhuman chemistry intuition and experimental capabilities.

Skills

ML fundamentals

Cross-disciplinary collaboration

Enthusiasm for full ML stack

Strong communication

Curiosity about chemistry

Tools

PyTorch

Job description

onepot is automating chemistry and building a self-improvement loop by combining AI and robotics. We are seeking a machine learning researcher to train the next generation of chemistry models and enable synthesis of previously inaccessible molecules.

You will work across the full modeling stack with lab staff on data acquisition, train diverse models, and deploy them into experimental workflows. Strong ML fundamentals and curiosity about chemistry are essential, with ownership in a startup