Develop and apply state-of-the-art machine-learning force fields for problems in therapeutics and materials. Build and manage large quantum-chemistry datasets, implement training and deployment software, extend ML force-field accuracy and generalization, and communicate results within an interdisciplinary team.
We’re seeking a Machine Learning (ML) Scientist to join us in our mission to transform the discovery of therapeutics and materials.
Schrödinger has pioneered a physics-based software platform that enables discovery of high-quality, novel molecules for drug development and materials applications more rapidly and at lower cost compared to traditional methods. The software platform is used by biopharmaceutical and industrial companies, academic institutions, and government laboratories around the world. Our multidisciplinary drug discovery team also leverages the software platform to advance collaborative programs and its own pipeline of novel therapeutics to address unmet medical needs.
As a member of our Machine Learning team, you’ll develop state-of-the-art ML force fields targeting impactful applications in Life and Materials sciences.
Who will love this job:
- An ML force fields expert who has developed, validated, and applied ML force fields to simulate complex condensed-phase systems, such as solid-liquid interfaces, reactive events in the condensed phase, or solvated biomolecules
- An innovator who’s driven to leverage technical knowledge to make a tangible impact
- A scientist with deep knowledge of both finite system and periodic DFT, as well as other electronic structure methods, and who understands the limitations and appropriate applications of these methods
- A proficient Python programmer with prior knowledge of ML toolkits such as PyTorch, Scikit-Learn, NumPy, SciPy, and Pandas
- An independent researcher who enjoys collaborating with an interdisciplinary team in a fast-paced environment
What you’ll do:
- Build and manage large data sets generated using quantum chemical methods at scale to develop predictive ML force fields
- Develop software that trains and applies ML force fields to challenging problems in life and materials sciences
- Extend the accuracy, capability and generalization of current ML force fields
- Communicate results and present ideas to the team
What you should have:
- A PhD (or extensive experience) in Chemistry, Materials Science, Engineering, Computer Science, or Physics
- A proven track record of scientific contribution and independent research
- Prior experience with development of ML force fields and/or electronic structure methods
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 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. 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: $120,000 - $175,000. 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, Inc. Cambridge, Massachusetts, USA Office
Schrödinger, Inc. Boston Office Office
222 3rd St, Cambridge, MA, United States
Similar Jobs at Schrödinger, Inc.
Healthtech • Machine Learning • Software • Biotech • Pharmaceutical
Develop and improve atomistic physics-based force fields for small molecules and proteins, collaborate with cross-functional teams and Schrodinger's AI tools, validate models with molecular simulation and QM methods, and write maintainable code following engineering best practices.
Top Skills:
BunsenC++Force Field ParameterizationMachine LearningMolecular SimulationPythonQm MethodsSchrodinger
Healthtech • Machine Learning • Software • Biotech • Pharmaceutical
Provide commercial legal support by drafting, reviewing, and negotiating SaaS, software license, services, vendor, partner, and confidentiality agreements. Advise sales and cross-functional teams on commercial, data privacy, cybersecurity, and AI-related issues. Build contracting templates, playbooks, and workflows; deliver training; monitor legal and regulatory developments; and support corporate governance and compliance projects as needed.
Top Skills:
Ai/MlCross-Border Data TransferCybersecurityData PrivacyGdprIntellectual PropertyOpen Source LicensingSaaSSoftware Licensing
Healthtech • Machine Learning • Software • Biotech • Pharmaceutical
Deploy, configure, and optimize molecular modeling and informatics applications in customer cloud/HPC environments. Provide technical solutions, maintain scientific computing resources, support installations and integrations, troubleshoot production issues, and collaborate with product managers, scientists, and developers.
Top Skills:
AWSBashContainerized WorkloadsDnsETLFirewallsFlat FilesGpu ComputingHpcJSONKubernetesLinuxNat GatewaysPythonRest ApisRoutingSaml/SsoSQLVpc
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
