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Together with our customers, we're on a mission to make healthcare better.
The Role
Design, build, and deploy cloud-native AI applications using LLMs, RAG, computer vision, and agentic AI. Develop backend services, data pipelines, OCR and CV solutions, train and productionize ML/DL models, implement MLOps (CI/CD, model versioning, monitoring), and collaborate with cross-functional teams to translate clinical/business requirements into scalable AI solutions.
Summary Generated by Built In
Work Flexibility: HybridWhat You Will Do
- Design, develop, and deploy AI-powered applications leveraging Generative AI, Large Language Models (LLMs), Computer Vision, Machine Learning, and Agentic AI technologies.
- Build scalable backend services, APIs, and workflow orchestration components for AI solutions.
- Design and implement Retrieval-Augmented Generation (RAG) pipelines, intelligent assistants, and workflow automation solutions.
- Develop Computer Vision and OCR solutions for image analysis, document digitization, information extraction, and automation workflows.
- Train, optimize, evaluate, and deploy machine learning and deep learning models for production use.
- Build data pipelines supporting AI model training, validation, and inference workflows.
- Develop cloud-native AI applications and deploy solutions on Azure and other cloud platforms.
- Implement MLOps best practices including model versioning, monitoring, CI/CD, and deployment automation.
- Collaborate with cross-functional teams to translate business and clinical requirements into scalable AI solutions.
- Create technical documentation, architecture diagrams, validation reports, and deployment artifacts.
- Stay current with advancements in AI, Computer Vision, LLMs, and Agentic AI.
- Bachelor's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Electrical Engineering, or a related field with 3+ years of relevant industry experience; OR
- Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, Electrical Engineering, or a related field.
- Strong programming skills in Python.
- Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
- Experience developing APIs, backend services, and distributed applications.
- Familiarity with Computer Vision techniques including OCR, image classification, segmentation, and object detection.
- Understanding of LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), and Agentic AI concepts.
- Experience working with structured and unstructured data and building data pipelines.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Knowledge of databases, version control systems, CI/CD pipelines, and software development best practices.
- Familiarity with Docker, Kubernetes, and MLOps concepts.
- Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning, or similar AI platforms.
- Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent AI frameworks.
- Experience building production-grade GenAI, RAG, OCR, or intelligent document processing solutions.
- Experience with MLflow, monitoring tools, and model lifecycle management.
- Exposure to healthcare, medical imaging, or regulated environments.
- Experience creating technical architecture documentation and contributing to solution design discussions.
Skills Required
- Bachelor's degree in Computer Science/AI/ML/Software/Electrical Engineering (with 3+ years relevant industry experience) OR Master's degree in related field
- 3+ years of relevant industry experience
- Strong programming skills in Python
- Experience with PyTorch or TensorFlow (deep learning frameworks)
- Experience developing APIs, backend services, and distributed applications
- Familiarity with Computer Vision techniques including OCR, image classification, segmentation, and object detection
- Understanding of LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), and Agentic AI concepts
- Experience working with structured and unstructured data and building data pipelines
- Experience with cloud platforms such as Azure, AWS, or GCP
- Knowledge of databases, version control systems, CI/CD pipelines, and software development best practices
- Familiarity with Docker, Kubernetes, and MLOps concepts
- Experience with model training, optimization, evaluation, and deployment for production use
- Ability to create technical documentation, architecture diagrams, validation reports, and deployment artifacts
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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