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
Skills Required
- BS, MS, or PhD in Computer Science, Machine Learning, Software Engineering, Mathematics, Physics, Chemistry, or a related field
Schrödinger, Inc. Compensation & Benefits Highlights
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Leave & Time Off Breadth — Company materials describe generous vacation with two companywide shutdown weeks, indicating broad time-off availability. Paid parental leave and flexible work norms further extend time-away and scheduling support.
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Healthcare Strength — The package includes medical, dental, vision, mental‑health benefits, an EAP, and FSAs, pointing to robust core coverage. Wellness-oriented elements and onsite perks reinforce health support beyond basics.
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Parental & Family Support — Paid parental leave plus subsidized backup care for children, elders, and pets, along with optional pet insurance, reflect wide-ranging family support. Return‑to‑work assistance and family-oriented events add practical caregiving flexibility.
Schrödinger, Inc. Insights
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.
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Schrödinger, Inc. Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.