Scientific ML Engineer — Drug Discovery & Materials

Schr; New York (NY); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Healthcare (dental & vision)

401k

Flexible schedule

Parental leave

Paid vacation

Company events

Job summary

Schrödinger is seeking a Scientific ML Engineer to design, build, and test scalable software for ML-driven discovery in chemistry and materials. You will integrate ML applications with physics-based backends like docking and free energy calculations to optimize hit discovery and lead optimization.

You will work closely with scientists to adapt workflows for new discovery cases, benchmark novel ML methods, and contribute to expanding our pipelines with new methodologies and best practices.

Qualifications

• Bachelor’s degree or higher in Chemistry, Physics, CS, or related field.
• 1–3 years of production-level software development experience.
• Prior ML knowledge (Reinforcement Learning or Active Learning) for predicting properties of biological/chemical systems.
• Python proficiency and experience with PyTorch.

Responsibilities

• Design, build, and test scalable software for ML pipelines.
• Integrate ML applications with physics-based backends to optimize hit and hit-to-lead campaigns.
• Collaborate with scientists to adapt and expand workflows for new discovery cases and develop new methodologies.

Skills

Python

PyTorch

Reinforcement Learning

Active Learning

Education

Bachelor's degree or higher in Chemistry, Physics, CS, or related field

Job description

Schrödinger is seeking a Scientific ML Engineer to design, build, and test scalable software for ML-driven discovery in chemistry and materials. You will integrate ML applications with physics-based backends like docking and free energy calculations to optimize hit discovery and lead optimization.

You will work closely with scientists to adapt workflows for new discovery cases, benchmark novel ML methods, and contribute to expanding our pipelines with new methodologies and best practices.