Work Flexibility: Hybrid

Position Overview

We are seeking a visionary Technical Manager with 15+ years of overall experience to lead our AI engineering team. You must bring 5 years of dedicated experience managing, mentoring, and scaling technical teams. In this role, you will drive the development, training, and deployment of cutting-edge AI models, with a specific focus on medical imaging applications. This role balances technical architecture, hands-on modeling strategy, and people leadership.

What you will do:

• Lead the end-to-end strategy for AI model development and production deployment.

• Evaluate and implement emerging AI frameworks, tools, and cloud methodologies.

• Oversee the training and optimization of deep learning models for imaging computer vision.

• Guide the team in handling 2D/3D medical modalities like MRI, CT, X-ray, and Ultrasound.

• Deep knowledge of deep learning for segmentation, detection, classification, registration, reconstruction, and longitudinal change analysis

• CNNs, Transformers, U-Net variants, nnU-Net, and foundation/self-supervised models for imaging.

• Architect robust MLOps pipelines for continuous model monitoring, testing, and deployment.

• Optimize models for cloud, edge, and clinical environment hardware constraints.

What you need:

Required Qualifications:-

• Master’s or Ph.D. in Computer Science, Biomedical Engineering, or a related field.

• 15+ years of experience in software engineering and data science.

• 5 years of direct experience managing and leading technical AI/ML teams.

• Strong research background with demonstrated contributions in AI/ML through publications, patents, applied research, industrial innovation, or equivalent scientific work.

• Deep knowledge of Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Large Language Models, Agentic AI / AI Agents

• Proven experience developing advanced AI models from research through implementation and evaluation.

Technical Skills

• Core AI: Deep understanding of CNNs, Transformers, segmentation, and object detection.

• Imaging Libraries: Expertise in DICOM, NIfTI, ITK, Monai, OpenCV, and PyTorch/TensorFlow.

• MLOps: Hands-on experience with Docker, Kubernetes, Triton, AWS, GCP, or Azure ML.

• Data Handling: Experience with medical data de-identification, curation, and active learning.

Preferred

• Strong communication skills to bridge the gap between technical teams and medical experts.

• Proven track record working with medical imaging data and clinical workflows.

• Knowledge of clinical workflow integration: PACS/RIS/VNA, DICOM networking, study routing, and integration with hospital IT systems

• Designed scalable infrastructure for processing high-resolution medical imaging datasets.

• Ensured compliance with medical software standards, data privacy, and security protocols.

Travel Percentage: None