Machine Learning Force Field Scientist
- Pay
- $120,000 – $175,000 per year
- Location
- New York, NY · Hybrid
- Job type
- Full-time
- Level
- Mid-level
- Education
- Doctorate
- Listed
- 30 days ago
Skills & highlights for this role
- PyTorch
- Python
- density functional theory
- machine learning force fields
Also useful
- Scikit-Learn
- NumPy
- SciPy
- Pandas
Stated benefits & perks
- Health
- Dental
- Vision
- 401k
- Parental leave
About the role
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 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!
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. 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.
Equal opportunity and legal notices
As an equal opportunity employer, Schrödinger hires outstanding individuals into every position in the company. 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.
From Schrödinger's careers page, first listed on Rolev.ai on October 10, 2026. Rolev.ai is not the employer.
How Rolev.ai helps with this application
Rolev.ai is a job search and application tool for US job seekers. For this Machine Learning Force Field Scientist role at Schrödinger, it shows how your resume fits, tailors your resume to the posting, and prepares the application for you to review.
See how you fit
Openings from employer career sites are ranked against your whole resume—and searchable inside Claude, ChatGPT, and Cursor via Rolev.ai MCP.
Tailor without inventing
Every change to your resume is checked against your original. New experience goes in only with your yes—zero fabricated claims.
Draft the full kit
Tailored and Full Match resumes, role-specific cover letters, and answers to employer screening questions are prepared in seconds.
1-Click Extension Autofill
The Chrome extension fills the employer's Greenhouse, Workday, Lever, or Ashby form in 1 click. You review it and press Submit.
Similar roles
- Member of Technical StaffBuild AI · San Francisco, CA
- ML Research Scientist (MLRS) - Generative AIAchira · San Francisco, CA
- Senior ML Research ScientistRad AI · San Francisco, CA
- Research ScientistSesame · San Francisco, CA
- Research Scientist, Machine Learning for Monetization (PhD)Meta · Sunnyvale, CA
- Machine Learning ScientistTacit · San Francisco, CA
Common questions
What is the salary for the Machine Learning Force Field Scientist role at Schrödinger?
The Machine Learning Force Field Scientist posting at Schrödinger states compensation of $120,000 – $175,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Schrödinger's official career site.
Where is the Machine Learning Force Field Scientist job at Schrödinger located?
This Machine Learning Force Field Scientist position at Schrödinger is located in New York, NY (Hybrid). Always check Schrödinger's application page for specific state eligibility or relocation policies.
What qualifications are required for Machine Learning Force Field Scientist at Schrödinger?
For the Machine Learning Force Field Scientist role, Schrödinger highlights a doctorate; experience with PyTorch, Python, density functional theory, machine learning force fields. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Machine Learning Force Field Scientist position at Schrödinger?
This listing links directly to Schrödinger's Greenhouse application page. You can apply directly on Schrödinger's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Greenhouse application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.