Job Description

Locations

• India, Bengaluru

Skills Required

• AI/MLintermediate
• PyTorchintermediate
• Python with hands-on experience in PyTorchintermediate
• inference optimizationintermediate
• cloud platforms such as AWSintermediate
• medical/healthcare domainintermediate

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field. (degree in master)
• 12–17 years of experience in AI/ML, computer vision, deep learning, or AI systems engineering. (experience, 17 years)
• Strong foundations in algorithms, system design, software engineering, model evaluation, and optimization. (experience)
• Advanced programming expertise in Python with hands-on experience in PyTorch or TensorFlow. (experience)
• Experience with inference optimization and deployment using TensorRT, ONNX, or OpenVINO. (experience)
• Familiarity with cloud platforms such as AWS or Azure and ML services such as AWS SageMaker or Azure ML. (experience)
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or a related field. (degree in master)
• 12–17 years of experience in AI/ML, computer vision, deep learning, or AI systems engineering. (experience, 17 years)
• Strong foundations in algorithms, system design, software engineering, model evaluation, and optimization. (experience)
• Advanced programming expertise in Python with hands-on experience in PyTorch or TensorFlow. (experience)
• Experience with inference optimization and deployment using TensorRT, ONNX, or OpenVINO. (experience)
• Familiarity with cloud platforms such as AWS or Azure and ML services such as AWS SageMaker or Azure ML. (experience)

Preferred Qualifications

• Experience leading agentic AI workflows or teams and reviewing AI-generated code and artifacts. (experience)
• Experience in the medical/healthcare domain or shipping AI/ML products in regulated environments with validation and risk management requirements. (experience)
• Experience leading agentic AI workflows or teams and reviewing AI-generated code and artifacts. (experience)
• Experience in the medical/healthcare domain or shipping AI/ML products in regulated environments with validation and risk management requirements. (experience)

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.
• 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.

Tags & Categories