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# Scientific Machine Learning Engineer

- **Company:** Schrodinger, Inc.
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $130,000.0 - $160,000.0
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, Code Review, Data Files, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Software Engineering, Reinforcement Learning, Pytorch, Information Technology
- **Published:** October 2, 2026
- **Apply:** https://dejobs.org/x/x/D96F89DFEE3B48DDB8554106701F56E9/job/

## About the Role

* 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, * 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, 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.

## Description

* 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