Principal Engineer - AI/ML - Computer Vision
Stryker
Bengaluru, Karnataka, IndiaPRINCIPAL
AIHealthcareMachine LearningComputer Vision
Job Description
Lead the end-to-end development of critical AI subsystems in healthcare.
Responsibilities
- 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.
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.
Nice to have
- 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.