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Senior Machine Learning Engineer - Intuitive (Intuitive Surgical)
ML Engineer
Lead end‑to‑end ML solutions for robotic‑assisted surgery, building scalable models in Python and TensorFlow, deploying them on AWS, and collaborating with cross‑functional teams to improve surgical precision and patient outcomes.
About the role
Key Responsibilities
- Design, develop, and production‑grade machine learning models that enhance robotic‑assisted surgical systems.
- Collaborate with data scientists, software engineers, and clinicians to define problem statements, collect and preprocess large medical datasets.
- Implement deep learning pipelines using TensorFlow/PyTorch, optimize models for inference latency and accuracy.
- Deploy models to AWS infrastructure (SageMaker, ECS, Lambda) ensuring scalability, security, and compliance with medical regulations.
- Monitor model performance in production, conduct A/B testing, and iterate on solutions based on real‑world feedback.
Requirements
- 5+ years of experience in machine learning engineering, preferably in medical or high‑reliability domains.
- Proficiency in Python, deep learning frameworks (TensorFlow or PyTorch), and cloud services (AWS).
- Strong background in data engineering, feature engineering, and model deployment pipelines.
- Excellent problem‑solving skills and ability to translate clinical needs into technical solutions.
- Effective communication skills to collaborate with multidisciplinary teams.
Skills
pythonmachine learningdeep learningtensorflowaws