Lead Machine Learning Engineer - Medical Imaging
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Role details
Tech stack
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Job description
We are looking for a Lead Machine Learning Engineer - Medical Imaging to lead a small ML research team developing novel imaging technologies.
This is a hands-on technical leadership role. We need someone who can set research direction, design experiments, develop and train models, mentor engineers, investigate failures, and help move successful research toward clinical and regulatory-ready products.
What You’ll Do
- Lead ML research and mentor a small team while remaining actively involved in coding, training, and experimentation.
- Develop and evaluate methods involving 2D/3D medical imaging, reconstruction, image analysis, and generative imaging.
- Work with medical imaging datasets including X-ray, CT, DICOM, annotations, masks, and volumetric data.
- Translate promising research papers into working implementations and controlled experiments.
- Design validation methods that distinguish clinically supported information from visually plausible model output.
- Address data quality, registration error, hallucination, domain shift, uncertainty, and other model failure modes.
- Build reproducible preprocessing, training, inference, and evaluation pipelines.
- Help move successful research toward production, clinical validation, and regulatory submission., Medical imaging also requires more than producing visually impressive results. We want someone who thinks carefully about what information is actually supported by the input data, what is being inferred by the model, how uncertainty should be handled, and how anatomical and clinical fidelity can be validated.
Requirements
- 6+ years of applied ML/computer-vision experience.
- Advanced Python and PyTorch skills.
- Strong hands-on experience developing and training deep-learning models.
- Experience with medical imaging or closely related scientific imaging.
- Experience with CT, X-ray, CBCT, MRI, PET/SPECT, ultrasound, or other volumetric imaging.
- Strong understanding of 2D/3D computer vision, experimental design, dataset partitioning, validation, and error analysis.
- Demonstrated ability to take an open-ended research problem from literature ? hypothesis ? implementation ? experimentation ? failure analysis ? improvement.
- Experience leading or mentoring ML engineers/researchers.
Particularly Valuable
Experience with several of the following would be especially relevant:
- CT reconstruction or inverse problems
- Diffusion models and other generative AI
- Medical-image registration
- DICOM pipelines
- CUDA/multi-GPU training
- Multi-site/scanner validation
- Published medical-imaging research or patents
- Production medical software
- FDA 510(k), SaMD, design controls, IEC 62304, or medical-device V&V
The Person We’re Looking For
We are not looking for a manager who has stopped being technical., A PhD in computer science, electrical engineering, biomedical engineering, medical physics, imaging science, applied mathematics, or a related field is highly desirable, but demonstrated research accomplishments and technical depth matter more than the credential itself.
Benefits & conditions
We offer competitive salaries commensurate with experience, plus extremely generous health care plan, as well as 401K and stock options.
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