Medtronic is looking to drive the strategic development of scalable AI and MLOps platforms for defect inspection and visual process monitoring across its diverse product portfolio, converting proof-of-concepts into production-grade solutions that ensure global scalability, reliability, and compliance in regulated manufacturing environments.
Requirements
- AWS SageMaker
- NVIDIA TAO Toolkit
- PyTorch
- Halcon
- OpenCV
- AWS SageMaker
- PyTorch
- MLOps toolchains ( ClearML , GitLab CI/CD, Docker, Kubernetes/EKS, Helm, Triton Inference Server)
- computer vision algorithm development
- data curation and annotation platforms (Voxel51, V7 )
- advanced imaging
- Industry 4.0/IoT cloud-to-edge AI architectures
- validation and performance analysis (MSA, IQ/OQ/PQ, TMV)
Responsibilities
- Define and execute the strategic roadmap for Analytics for Manufacturing Imaging , including data ingestion, annotation governance, model training, deployment, and lifecycle management.
- Architect end-to-end workflows in AWS SageMaker, NVIDIA TAO Toolkit , PyTorch , and other custom training pipelines , ensuring reproducibility, scalability, and regulatory compliance.
- Develop advanced computer vision solutions, including segmentation, anomaly detection, and transformer-based vision models , while integrating hybrid approaches using Halcon and OpenCV
- Prototype and adapt foundation models (e.g., DINOv2, SAM 2.1) using transfer learning and self-supervised methods , translating research into validated, domain-specific solutions for manufacturing.
- Lead initiatives to operationalize DataOps automation and model-assisted annotation to accelerate high-quality ground-truth creation.
- Plan and direct AI/ML model from experimentation to deployment, ensuring performance benchmarking, validation, and compliance with medical device quality standards.
- Provide strategic leadership for the Manufacturing Imaging & Analytics Center of Excellence , setting best practices and enabling adoption of AI/ML solutions at global manufacturing sites.
Other
- The ability and self-motivation to take a strategy and vision , define and manage project deliverables , and deliver scalable project outcomes
- Excellent communication and knowledge-sharing skills, with experience building Centers of Excellence, technical standards, and training frameworks .
- Ability to collaborate effectively with a wide range of stakeholders and internal customers, from manufacturing process to quality and automation engineers
- Minimum of 4 days a week onsite as part of our commitment to fostering a culture of professional growth and cross-functional collaboration
- Bachelor’s Degree and 7+ years of AI/ML engineering experience, including computer vision and MLOps , OR advanced degree with 5+ years of experience.
