remote
Machine Learning Engineer - Intuitive (Intuitive Surgical)
ML Engineer
Machine Learning Engineer building robust, scalable models for robotic‑assisted surgery, leveraging Python, TensorFlow/PyTorch, and cloud MLOps to deliver real‑time insights and improve surgical outcomes.
About the role
Key Responsibilities
- Design, develop, and deploy end‑to‑end machine learning pipelines for surgical robotics applications.
- Collaborate with cross‑functional teams to translate clinical requirements into data‑driven solutions.
- Implement and maintain production‑grade models using TensorFlow/PyTorch, ensuring performance, reliability, and safety.
- Integrate models into cloud environments (AWS/GCP) and manage continuous integration/continuous deployment (CI/CD) workflows.
- Analyze large medical datasets, engineer features, and conduct rigorous model validation and testing.
Requirements
- BS/MS in Computer Science, Engineering, or related field with strong quantitative background.
- 3+ years of experience building production ML systems in Python.
- Proficiency with deep learning frameworks (TensorFlow, PyTorch) and MLOps tools.
- Experience with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).
- Excellent problem‑solving skills and ability to work in a fast‑paced, interdisciplinary environment.
Skills
pythonmachine learningdeep learningtensorflowpytorchmlops