Lead the end-to-end development of critical AI subsystems in healthcare, from algorithmic direction through implementation, validation, optimization, and deployment readiness.
Translate business and open-ended requirements into clear technical strategies and execution plans.
Drive agent-assisted development by leveraging agentic AI to accelerate execution while maintaining accountability for technical outcomes.
Critically review AI-generated code and artifacts to ensure technical rigor, quality, and reliability.
Design and implement scalable, high-performance AI/ML and computer vision solutions.
Oversee model evaluation, inference optimization, and deployment for real-world applications.
Collaborate with cross-functional, different geographically located teams to deliver robust AI solutions aligned with business and regulatory requirements.
Identify technical risks early and ensure timely, high-quality delivery of AI subsystems.
Required Qualifications-
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field.
12–17 years of experience in AI/ML, computer vision, deep learning, or AI systems engineering.
Strong foundations in algorithms, system design, software engineering, model evaluation, and optimization.
Advanced programming expertise in Python with hands-on experience in PyTorch or TensorFlow.
Experience with inference optimization and deployment using TensorRT, ONNX, or OpenVINO.
Familiarity with cloud platforms such as AWS or Azure and ML services such as AWS SageMaker or Azure ML.
Preferred Qualifications-
Experience leading agentic AI workflows or teams and reviewing AI-generated code and artifacts.
Experience in the medical/healthcare domain or shipping AI/ML products in regulated environments with validation and risk management requirements.
Skills Required
- Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Electrical Engineering, or related field
- 12-17 years of experience in AI/ML, computer vision, deep learning, or AI systems engineering
- Advanced programming expertise in Python with hands-on experience in PyTorch or TensorFlow
- Experience with inference optimization and deployment using TensorRT, ONNX, or OpenVINO
- Familiarity with cloud platforms such as AWS or Azure
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 — Healthcare coverage is described as comprehensive, with multiple medical plan options and added protections such as critical illness, accident, and hospital indemnity, plus mental health resources. Wellbeing programs, onsite gyms, and fitness/nutrition classes further reinforce the perceived strength of health benefits.
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Retirement Support — Retirement offerings are seen as strong, highlighted by a competitive 401(k) plan with company matching and potential discretionary contributions. These elements are often viewed as valuable pillars of total rewards.
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Strong & Reliable Incentives — Variable pay is viewed positively, with annual bonuses and sales commissions often lifting total compensation. Incentive plans are seen as a meaningful contributor to pay satisfaction in roles where performance drives earnings.
Stryker Insights
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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