ML Software Engineer
Core
Building and applying non-hosted ML systems for image data and training data processing pipelines in the life sciences domain.
Role type
ML Software Engineer
Builds
ML systems and data processing pipelines for image data
Domain
Life sciences, Computer Vision
Deliverable
production ML models
Required skills
Python, PyTorch, software engineering best practices, MLOps lifecycles, training data processing pipelines
Preferred skills
TypeScript/Node/JavaScript, experiment tracking platforms, Kubeflow, AWS, regulated environment development
Technologies
PyTorch, TensorFlow, JAX, OpenCV, Kubeflow, AWS, Weights & Biases, MLFlow
Responsibilities
Build and apply ML systems with frameworks like PyTorch and TensorFlow; develop training data processing pipelines for image data; manage MLOps lifecycles including model training, validation, deployment, and quality monitoring; write high-performant, bug-free code with proper documentation and unit testing
Seniority
Individual Contributor