remote
Staff Machine Learning Engineer - Intuitive (Intuitive Surgical)
ML Engineer
Lead the design and deployment of advanced machine‑learning models for robotic surgery systems, leveraging Python, C++, deep‑learning frameworks, and cloud infrastructure.
About the role
Key Responsibilities
- Architect, develop, and productionize machine‑learning algorithms that enhance perception, control, and decision‑making in robotic surgical platforms.
- Collaborate with cross‑functional teams of surgeons, hardware engineers, and software developers to define data requirements and model performance targets.
- Design and implement scalable data pipelines and training workflows on AWS, ensuring reproducibility and compliance with medical‑device regulations.
- Lead model validation, testing, and continuous monitoring in real‑time operating environments, driving iterative improvements.
- Mentor senior engineers and researchers, fostering best practices in code quality, version control, and scientific rigor.
Requirements
- Ph.D. or Master’s in Computer Science, Electrical Engineering, Robotics, or related field with 8+ years of hands‑on ML experience.
- Expertise in Python and C++ for building high‑performance ML pipelines and integrating models into embedded systems.
- Deep knowledge of TensorFlow or PyTorch, including model optimization, quantization, and deployment on edge devices.
- Proven experience with cloud platforms (AWS) for data storage, distributed training, and CI/CD of ML models.
- Strong track record of publishing or delivering ML solutions in safety‑critical or regulated environments.
Skills
pythonctensorflowpytorchdeep learningaws