Schrödinger, Inc.

Machine Learning Platform Engineer

Posted 4 Days Ago

New York, NY

Hybrid

120K-145K Annually

Mid level

Healthtech • Machine Learning • Software • Biotech • Pharmaceutical

Opening new worlds for molecular discovery

The Role

Develop scalable ML platform infrastructure, support ML training and deployment, collaborate on software tools for scientists, and enhance workflows and automation.

Summary Generated by Built In

Schrödinger seeks a Machine Learning (ML) Platform Engineer to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods!

As a member of the Machine Learning team, you’ll build scalable software systems that enable scientists and engineers to train, deploy, and analyze machine learning models at scale. Our machine learning platform, LiveDesignML, supports applications ranging from molecular property prediction and generative chemistry to protein modeling.

Who will love this job:

A highly-skilled software engineer who understands coding fundamentals, is experienced with Python, and has run projects end-to-end, from prototype to production
An ML expert who’s familiar with PyTorch, TensorFlow, and scikit-learn
An analytical thinker who enjoys working with multi-dimensional data, solving data-processing problems, and digging through complex systems to solve technical problems
A polymath who’s excited about working collaboratively in an interdisciplinary environment and comfortable with self-directed research and problem exploration

What you’ll do:

Design and develop infrastructure supporting machine learning training, inference, and experimentation workflows
Build and maintain production systems that enable scientists to run large-scale ML workloads
Collaborate with scientists, ML researchers, and engineers to translate research ideas into reliable software tools
Contribute to backend services and APIs supporting ML workflows and platform features
Improve developer workflows, testing infrastructure, and deployment automation
Participate in code reviews and contribute to engineering best practices across the team
Pitch in on frontend components of the ML platform web interface when needed

What you should have:

BS, MS, or PhD in Computer Science, Machine Learning, Software Engineering, Mathematics, Physics, Chemistry, or a related field

Experience with the following is nice to have, but not required:

Cloud platforms like AWS or GCP
Containerization and orchestration (e.g., Docker, Kubernetes, Argo Workflows, Helm charts, etc.)
CI/CD systems and modern software development workflows (e.g., Jenkins, GitHub Actions, etc.)
Monitoring, logging, or observability systems
Distributed computing or large-scale ML workloads
ML training pipelines or experiment management
Data processing pipelines or large-scale data analysis
Source control systems (Git or similar)
Web application development (e.g., React, TypeScript, REST APIs)
Interest in scientific computing, chemistry, biology, physics, or related domains

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 - $145,000. 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.

Top Skills

AWS

Docker

GCP

Kubernetes

Python

PyTorch

Scikit-Learn

TensorFlow

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The Company

HQ: New York, NY

885 Employees

Year Founded: 1990

What We Do

Schrödinger is a leading provider of advanced molecular simulations and enterprise software solutions and services for pharmaceutical, biotechnology, and materials science research. The predictive power of Schrödinger's software allows scientists to accelerate their research and development, reduce research costs, and make novel discoveries.

Why Work With Us

We have a mission-driven culture that thrives off team collaboration. By utilizing a non-hierarchal approach, we hope to give all employees a voice and room to grow to their fullest potential. We actively engage in diversity and inclusion efforts, pay fairly, and always strive to provide a supportive atmosphere for our teams.