Schrödinger
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
To apply for this job please visit job-boards.greenhouse.io.
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Working in New York, NY
New York, often called New York City (NYC), is the most populous city in the United States. It is located at the southern tip of New York State on New York Harbor, one of the world's largest natural harbors. The city comprises five boroughs—Manhattan, Brooklyn, Queens, the Bronx, and Staten Island; each is coextensive with its respective county. It is the geographical and demographic center of both the Northeast megalopolis and the New York metropolitan area, the largest metropolitan area in the United States by both population and urban area. New York is a global center of finance and commerc
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