We’re seeking a Scientific Machine Learning (ML) Engineer to join us in our mission to transform the discovery of therapeutics and materials!

Our Hit Discovery team builds computational workflows that combine machine learning with chemical physics to efficiently evaluate billions of potential drug molecules. As a member of this group, you’ll collaborate with research scientists on improving the accuracy and applicability of these methods and turn them into robust, scalable software products.

Who will love this job:

An applied problem solver who’s excited about addressing challenging problems in computational chemistry and thrives when working with large codebases and data sets
A growth-oriented engineer who’s eager to adopt best practices like automated testing and code reviews
A collaborative communicator who enjoys bridging the gap between ML, software engineering, and scientific research

What you’ll do:

Design, build, and test scalable software for ML virtual screening pipelines, integrating ML applications with physics-based backends (such as docking and free energy perturbation) to optimize hit and hit-to-lead campaigns
Work closely with scientists to adapt and expand our existing workflows for new discovery cases, as well as help develop new methodologies with our current pipelines
Explore scientific literature and benchmark novel ML approaches to improve the applicability and accuracy of core hit discovery workflows

What you should have:

Bachelor’s degree or higher in Chemistry, Physics, Computer Science, or a related field
Between one and three years of production-level software development experience
Prior ML knowledge (i.e., Reinforcement Learning or Active Learning) for predicting measurable properties of biological and/or chemical systems
Python programming proficiency and experience with ML frameworks like PyTorch

We’d love to hire someone with:

Familiarity with one of the following areas: molecular dynamics simulation, free energy calculation methods, ligand-based drug design, cheminformatics, quantum mechanics, virtual screening, and/or structured modeling
Experience with development of relevant commercial and/or open-source computational chemistry software

Pay and perks:

Schrödinger understands it’s people that make a company great. Because of this, we’re prepared to offer a competitive salary, equity-based compensation, and a wide range of benefits that include healthcare (with dental and vision), a 401k, pre-tax commuter benefits, a flexible work schedule, and a parental leave program. We have a company culture that is relaxed, but engaged, and over a month of paid vacation time. Our Office Management team also plans a myriad of fun company-wide events. New York is home to our largest office, but we have teams all over the world. Schrödinger is honored to have been included in Crain's New York Best Places to Work, BuiltIn's NYC Best Place to Work, and Newsweek's list of America's 100 Most Loved Workplaces.

Estimated base salary range: $130,000 - $160,000. Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs. If you have any questions regarding the compensation for this role, do not hesitate to reach out to a member of our Strategic Growth team.

Sound exciting? Apply today and join us!

As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. People who work with us have a high degree of engagement, a commitment to working effectively in teams, and a passion for the company's mission. We place the highest value on creating a safe environment where our employees can grow and contribute, and refuse to discriminate on the basis of race, color, religious belief, sex, age, disability, national origin, alienage or citizenship status, marital status, partnership status, caregiver status, sexual and reproductive health decisions, gender identity or expression, sexual orientation, or any other protected characteristic. To us, "diversity" isn't just a buzzword, but an important element of our core principles and key business practices. We believe that diverse companies innovate better and think more creatively than homogenous ones because they take into account a wide range of viewpoints. For us, greater diversity doesn't mean better headlines or public images - it means increased adaptability and profitability.

Schrödinger

Scientific Machine Learning Engineer

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Schrödinger

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