Scientific Machine Learning Engineer

Job overview

Scientific Machine Learning Engineer is listed as an onsite role in New York, NY; the specific city is not stated. The estimated base salary range is $130,000–$160,000 annually. The role supports Schrödinger's Hit Discovery team and its mission to transform therapeutic and materials discovery. The engineer builds scalable machine-learning software for virtual screening workflows, combining machine learning with chemical physics to evaluate potential drug molecules. The role works with research scientists to improve existing methods, develop workflows for new discovery cases, and benchmark approaches for accuracy and applicability.

What you'll do

• Design, build, and test scalable software for machine-learning virtual screening pipelines
• integrate machine-learning applications with physics-based backends such as docking and free-energy perturbation
• collaborate with scientists to adapt workflows and develop methods
• review scientific literature and benchmark machine-learning approaches.

What we're looking for

Skills & competencies

scientific machine learning engineer

machine learning

computational chemistry

new york ny

schrödinger

python

pytorch

virtual screening

drug discovery

chemical physics

scalable software

annual salary $130,000–$160,000

healthcare

401(k)

Work arrangement

• Weekend coverage required

Benefits & perks

• Healthcare including dental and vision, 401(k), pre-tax commuter benefits, flexible work schedule, parental leave, and over a month of paid vacation.

Why this role

The role combines machine learning with computational chemistry and chemical physics for drug discovery workflows.

About the employer

Schrdinger is hiring for this role. Industry: Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology). Sector: 54.