Senior Machine Learning Engineer
Core
Build production-grade ML services, APIs, and applications to integrate predictive models into biologics discovery platforms and scientific workflows.
Role type
Senior Machine Learning Engineer (MLOps & Production)
Builds
Scalable, tested, and maintainable ML services and APIs for Large Molecule Discovery
Domain
Biotechnology / Bioinformatics / Computational Chemistry
Deliverable
production ML models
Required skills
Python, MLOps tools (MLflow, model registries, CI/CD), Docker, Kubernetes, REST/gRPC APIs, Cloud platforms (AWS, Databricks, Spark), Model observability, ML frameworks (PyTorch, TensorFlow, scikit-learn)
Preferred skills
Experience with production ML systems, model-serving platforms, data-driven applications, model lifecycle management, production troubleshooting, open-source MLOps tools, publications in top ML venues
Technologies
MLflow, Docker, Kubernetes, AWS, Databricks, Spark, PyTorch, TensorFlow, scikit-learn, REST, gRPC
Responsibilities
Design, build, and deploy production-grade ML services and APIs; Package, containerize, and serve models for batch and real-time inference; Establish MLOps practices for experiment tracking, model/version management, validation, deployment, and rollback; Implement CI/CD pipelines to ensure code quality and reproducibility; Monitor model performance, data quality, drift, and service health; Build reproducible workflows for data preparation, training, inference, and evaluation; Evaluate and implement emerging MLOps and observability technologies
Seniority
Senior, hands-on IC
