Applied AI/ML Lead

Join Us in Revolutionizing Cardiac Care from Beautiful Santa Cruz Imagine bringing AI capabilities to life-saving robotics technology while being minutes from world-class surf breaks and redwood forests. We’re developing a groundbreaking robotic platform that gives surgeons superhuman precision in transcatheter valve deployment—and we need an Applied AI/ML Lead to help us integrate machine learning into our product for the first time. This is a foundational hire. You’ll be the internal expert on AI/ML, but your primary job isn’t to train neural networks from scratch—it’s to understand the rapidly evolving AI/ML landscape, identify opportunities for our product, work with third-party partners who build ML algorithms, and integrate those capabilities into our robotic platform. We need a strong software engineer who can own the technical integration end-to-end, with enough ML depth to be a credible technical counterpart to our partners and to evaluate what’s possible. What You’ll Do: - Stay current on advances in AI/ML as applied to medical imaging (X-ray, 3D echo, CT) and identify opportunities to bring these capabilities into our product - Own relationships with third-party ML and imaging partners—define requirements, evaluate their work, and hold them accountable for deliverables - Integrate ML models and AI-enabled features into our robotic software platform, ensuring they work reliably in a real-time clinical environment - Translate clinical and engineering requirements into practical ML problem statements that external partners can execute against - Evaluate ML model performance, define acceptance criteria, and support validation activities for regulatory submissions - Collaborate cross-functionally with software, robotics, controls, and clinical teams to ensure ML outputs are useful and well-integrated into procedural workflows - Build internal tooling and infrastructure for model evaluation, data management, and integration testing - Contribute to longer-term AI/ML roadmap planning and help define when to build vs. buy vs. partner Skills: - Excellent software engineering fundamentals: you write clean, maintainable, production-quality code - Strong Python skills with experience integrating ML models into larger software systems - Familiarity with modern ML frameworks (PyTorch, TensorFlow) and the ability to evaluate model architectures and performance - Understanding of computer vision and medical imaging concepts—you can speak credibly with imaging specialists and ML researchers - Experience managing technical vendor relationships or collaborating with external development partners - Strong communication skills—you can translate between clinical needs, engineering constraints, and ML capabilities - Ability to read and synthesize ML research papers and assess applicability to real-world problems - Comfortable working in ambiguity and defining the path forward in a new problem space Preferred: - Prior experience with medical imaging data (X-ray, ultrasound, echo, CT, MRI) - Experience shipping ML-enabled products in a regulated or safety-critical environment - Familiarity with model validation and documentation requirements for medical devices - Exposure to robotics, real-time systems, or image-guided procedures - Experience building data pipelines or ML infrastructure - Background in applied ML, even if not your primary focus