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Together with our customers, we're on a mission to make healthcare better.
The Role
Lead and scale an AI engineering team to develop, train, optimize, and deploy deep learning models for 2D/3D medical imaging. Drive model architecture choices (CNNs, Transformers, U-Net variants), implement MLOps pipelines, ensure cloud/edge clinical deployment, and collaborate with clinicians to integrate solutions into PACS/RIS workflows while meeting data privacy and compliance needs.
Summary Generated by Built In
Work Flexibility: HybridPosition OverviewWe are seeking a visionary Technical Manager with 15+ years of overall experience to lead our AI engineering team. You must bring 5 years of dedicated experience managing, mentoring, and scaling technical teams. In this role, you will drive the development, training, and deployment of cutting-edge AI models, with a specific focus on medical imaging applications. This role balances technical architecture, hands-on modeling strategy, and people leadership.What you will do:
- Lead the end-to-end strategy for AI model development and production deployment.
- Evaluate and implement emerging AI frameworks, tools, and cloud methodologies.
- Oversee the training and optimization of deep learning models for imaging computer vision.
- Guide the team in handling 2D/3D medical modalities like MRI, CT, X-ray, and Ultrasound.
- Deep knowledge of deep learning for segmentation, detection, classification, registration, reconstruction, and longitudinal change analysis
- CNNs, Transformers, U-Net variants, nnU-Net, and foundation/self-supervised models for imaging.
- Architect robust MLOps pipelines for continuous model monitoring, testing, and deployment.
- Optimize models for cloud, edge, and clinical environment hardware constraints.
- Master’s or Ph.D. in Computer Science, Biomedical Engineering, or a related field.
- 15+ years of experience in software engineering and data science.
- 5 years of direct experience managing and leading technical AI/ML teams.
- Strong research background with demonstrated contributions in AI/ML through publications, patents, applied research, industrial innovation, or equivalent scientific work.
- Deep knowledge of Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Large Language Models, Agentic AI / AI Agents
- Proven experience developing advanced AI models from research through implementation and evaluation.
- Core AI: Deep understanding of CNNs, Transformers, segmentation, and object detection.
- Imaging Libraries: Expertise in DICOM, NIfTI, ITK, Monai, OpenCV, and PyTorch/TensorFlow.
- MLOps: Hands-on experience with Docker, Kubernetes, Triton, AWS, GCP, or Azure ML.
- Data Handling: Experience with medical data de-identification, curation, and active learning.
- Strong communication skills to bridge the gap between technical teams and medical experts.
- Proven track record working with medical imaging data and clinical workflows.
- Knowledge of clinical workflow integration: PACS/RIS/VNA, DICOM networking, study routing, and integration with hospital IT systems
- Designed scalable infrastructure for processing high-resolution medical imaging datasets.
- Ensured compliance with medical software standards, data privacy, and security protocols.
Skills Required
- Master's or Ph.D. in Computer Science, Biomedical Engineering, or related field
- 15+ years of experience in software engineering and data science
- 5+ years of direct experience managing and leading technical AI/ML teams
- Strong research background with publications, patents, applied research, or equivalent
- Deep knowledge of Machine Learning, Deep Learning, NLP, Generative AI, LLMs, and Agentic AI
- Proven experience developing advanced AI models from research through implementation and evaluation
- Deep understanding of CNNs, Transformers, segmentation, detection, classification, registration, reconstruction
- Expertise with imaging libraries/formats: DICOM, NIfTI, ITK, MONAI, OpenCV
- Experience with PyTorch and/or TensorFlow
- MLOps experience: Docker, Kubernetes, Triton, and cloud ML platforms (AWS, GCP, Azure ML)
- Experience with medical data de-identification, curation, and active learning
- Strong communication skills to bridge technical teams and medical experts
- Proven track record working with medical imaging data and clinical workflows
- Knowledge of PACS/RIS/VNA, DICOM networking, study routing, hospital IT integration
- Experience designing scalable infrastructure for high-resolution medical imaging datasets
- Experience ensuring compliance with medical software standards, data privacy, and security protocols
Stryker Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stryker and has not been reviewed or approved by Stryker.
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Healthcare Strength — Multiple medical plan options with HSA support and global mental‑health access indicate broad, accessible care. These features materially enhance the overall value of the total‑rewards package.
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Retirement Support — A meaningful 401(k) company match with potential additional company contribution, alongside an ESPP, supports long‑term savings and wealth building. Documented plan specifics help employees understand eligibility, timing, and vesting mechanics.
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Parental & Family Support — Paid parental and caregiver leave, adoption and surrogacy assistance, and practical supports like breast milk shipping reflect a comprehensive, family‑friendly approach. These offerings address varied family‑building paths and caregiving needs.
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The Company
What We Do
Stryker is a global leader in medical technologies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in MedSurg, Neurotechnology, Orthopaedics and Spine that help improve patient and healthcare outcomes. Alongside its customers around the world, Stryker impacts more than 130 million patients annually. More information is available at www.stryker.com. Together with our customers, we are driven to make healthcare better.
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