Work Flexibility: Hybrid or Onsite

What You Will Do:

• 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.

What You Need:

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.

Travel Percentage: 10%