Machine Learning Engineer

Company OverviewEmbark on an enriching journey with PROCEPT BioRobotics, where our vision, mission, and values guide everything we do as a company. We are committed to revolutionizing treatment for benign prostatic hyperplasia (BPH, otherwise known as prostate gland enlargement) through innovation in surgical robotics. As our company succeeds and grows, we improve the quality of life of patients, provide more effective treatment options for surgeons, uphold the trust of our shareholders. That starts with a commitment to our People with a focus on creating an evolving landscape for your career, brimming with transformative opportunities that provide continuous career growth opportunities.
The Opportunity That Awaits YouAre you ready to revolutionize treatment for men suffering from BPH (Benign Prostatic Hyperplasia)? At PROCEPT, we are building the next generation of intelligent surgical systems—and you could be a key part of that transformation.
As a Machine Learning Engineer, you will design, develop, and deploy advanced machine learning models that power real-time image-guided robotics. Your work will directly impact surgical decision-making, automate clinical workflows, and enhance patient outcomes.You'll collaborate with top engineers, clinicians, and product leaders to bring AI to life in the operating room. This is your opportunity to join a mission-driven team where innovation matters—and where your code can save lives.
What You'll DoMachine Learning & Computer Vision-Design, train, and optimize ML models for tasks such as segmentation, object detection, classification, and image enhancement.-Leverage deep learning architectures including CNNs, transformers, and GANs to solve vision challenges in real-time surgical applications.-Apply techniques such as YOLO, Faster R-CNN, U-Net, and ResNet to process high-resolution ultrasound and MRI data. -Develop and integrate AI algorithms for surgical video, multi-modality image fusion, and 3D reconstruction.-Design, train, and fine-tune foundation models such as DINO, SAM, or MAL for computer vision and data scaling.-Build and evaluate models that learn from multiple modalities.
Full Lifecycle Model Development-Lead end-to-end ML workflows: data curation, preprocessing, training, evaluation, and deployment.-Collaborate with engineers to integrate ML models into production C++ pipelines and real-time systems.-Optimize inference performance and ensure robustness, reproducibility, and traceability of results.
Cross-Functional Collaboration-Work closely with product managers, clinical experts, software engineers, and hardware teams to align technical development with clinical needs.-Translate healthcare challenges into AI-driven solutions that improve surgical workflows and outcomes.-Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Research & Innovation-Stay current with the latest ML research in computer vision, medical imaging, and robotics.-Evaluate emerging approaches in unsupervised/self-supervised learning and privacy-preserving ML.-Contribute to intellectual property and scientific publications, where appropriate.
Ethical and Reliable AI-Champion the development of explainable, fair, and clinically trustworthy models.-Design data pipelines and algorithms that mitigate bias and ensure reproducibility in healthcare applications.

What We're Looking For Required Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field (PhD preferred).
• 4+ years (2+ years if PhD with computer vision research)  of experience in ML model development for computer vision—industry or postdoctoral research. 
• Strong Python and C++ programming skills; experience integrating models into production systems.
• Proficiency in deep learning frameworks such as PyTorch, TensorFlow, or Keras.
• Hands-on experience with medical imaging modalities (MRI, ultrasound) or a strong willingness to learn.
• Solid understanding of model evaluation, hyperparameter tuning, and dataset curation.
• Familiarity with database systems for managing large-scale medical image datasets.
• Ability to work in agile, cross-disciplinary environments and manage technical tasks in Jira or similar tools.

Preferred Qualifications

• Published work or patents in the field of AI for healthcare or medical imaging.
• Experience with video analysis, temporal models, or multi-modal data fusion.
• Strong background in image registration, tracking, or 3D model reconstruction.
• Familiarity with image processing libraries (e.g., OpenCV, ITK, SimpleITK).
• Experience deploying models on edge devices or embedded systems for real-time inference.
• Knowledge of explainability tools (e.g., Grad-CAM, SHA