AI/ML Engineer I

You’ll join our AI team to develop deep learning algorithms for image-guided interventions across the full range of radiological imaging - X-ray, CT, MRI and US. Working alongside AI scientists, software engineers, and clinicians, you’ll take algorithms from research through validation and into FDA-cleared products. This is a hands-on role with broad exposure to the full ML lifecycle in a startup environment.

What You’ll Do

• Design, train, and evaluate deep learning models for segmentation, landmark detection, registration, and 3D anatomical modeling
• Develop AI supporting image-guided interventions including surgical planning, navigation, and tumor ablation
• Build image processing pipelines for DICOM/NIfTI volumetric data across X-ray, CT, and MRI
• Analyze large clinical imaging datasets and improve data quality
• Design reproducible experiments and evaluate performance with appropriate statistical methods
• Write production-quality, well-tested code and collaborate with engineering on integration
• Support V&V activities for regulated medical device development

• Bachelor’s in CS, Biomedical/Electrical/Computer Engineering, Applied Math, Physics, or related
• 2+ years professional or graduate research experience in medical image analysis, computer vision, or deep learning (graduate research and internships count)
• Proficiency in Python, PyTorch, NumPy, Git
• Experience with at least one medical imaging library: MONAI, ITK/SimpleITK, VTK, or OpenCV
• Familiarity with DICOM/NIfTI and 3D volumetric images (CT, MRI, X-ray)
• Working knowledge of CNNs, U-Net, Vision Transformers, segmentation, and registration
• Comfortable in Linux environments, * Master’s in a related field
• 3D deep learning; nnU-Net, MONAI, TorchIO, or TotalSegmentator
• Model optimization: CUDA, TensorRT, ONNX
• Docker and cloud (GCP/Vertex AI a plus given our current migration; AWS also relevant)
• Reproducible ML pipelines and experiment tracking (MLflow, W&B)
• Annotation tooling (3D Slicer, ITK-SNAP)
• Regulated medical device development; familiarity with IEC 62304, ISO 13485, or GMLP
• Open-source contributions or publications

Pulled from the full job description

• 401(k)
• Health insurance
• Paid time off
• Health savings account, Your work ships in commercial, FDA-cleared devices used in real surgical workflows - not just papers. You’ll get end-to-end exposure from research through regulatory validation, work directly with leading device OEMs and clinicians, and have a highly visible impact at a fast-growing startup. Fully remote within the US.

We value engineers comfortable wearing multiple hats - taking ownership across algorithm development, software engineering, and data analysis, and learning new tools quickly.

Pay: $120,000.00 - $150,000.00 per year

Benefits:

• 401(k)
• Health insurance
• Health savings account
• Paid time off

ProVoyance builds AI-driven medical imaging software that converts radiological scans into detailed 3D anatomical models for procedure planning and navigation. In 2021 we received FDA clearance for one of the first AI-powered preoperative planning systems in orthopedics, and our platform now supports a broader range of image-guided interventions. We license our digital surgery platform - automated segmentation, planning, and navigation - to medical device manufacturers worldwide, partnering with companies across the field internationally to integrate AI into their imaging and robotic surgical systems.