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 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:-

• Masters 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.