Schrödinger, Inc.

Retrosynthesis Researcher, Machine Learning

New York

Sponsorship not specified$120k-$145kDetected 70 days ago

PythonAlgorithmsMachine LearningDeep LearningTensorFlowPyTorchNLPResearchAdaptability

About the role

As a member of our Machine Learning team, you'll work at the forefront of computational chemistry and AI, contributing to high-impact research with real-world applications in small molecule drug discovery and materials science.
We have regular catered meals in the office, 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.

Develop and implement AI/ML models (e.g., graph neural networks, transformer-based models) for retrosynthetic pathway prediction
Curate and manage reaction datasets from literature, patents, and proprietary sources to train and validate predictive models
Collaborate with synthetic chemists to experimentally validate predicted retrosynthetic routes and optimize laboratory workflows

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.
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.

Familiarity with chemical reaction databases (e.g., Reaxys, USPTO, Pistachio)
Knowledge of computer-aided synthesis planning (CASP) tools and retrosynthetic analysis software (e.g., AiZynthFinder, ASKCOS, IBM RXN)
Familiarity with reaction condition prediction and reaction yield optimization.
Experience with Schrödinger Suite and LiveDesign
Experience with cloud computing and/or high-performance computing (HPC) resources
Exposure to quantum chemistry (DFT) is a plus

An experienced user of cheminformatics tools (e.g., RDKit, Open Babel)
A proficient Python programmer who's familiar with ML tools like Pytorch, Tensorflow, and JAX
An excellent problem-solver who's comfortable working collaboratively in a multidisciplinary research environment

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.
$120,000 - $145,000.
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.

Apply deep learning techniques to predict reaction outcomes, optimize reaction conditions, and identify novel synthetic routes
A background in graph-based learning, attention mechanisms, and transformer architectures applied to chemical data
Experience with de novo design and generative machine learning methods
Pay and perks:
Actual compensation package is dependent on a number of factors, including, for example, experience, education, degrees held, market data, and business needs.

As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company.

efuse 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 he

This listing is sourced directly from Schrödinger, Inc.'s careers page and normalized into a canonical job model.