Machine Learning Platform Engineer
Indexed description
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
- 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
- BS, MS, or PhD in Computer Science, Machine Learning, Software Engineering, Mathematics, Physics, Chemistry, or a related field
- 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
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.
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