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%
