Senior Software developer

Description

The AI/ML Engineer will lead the design and implementation of advanced imaging algorithms for a next-generation healthcare platform focused on 3D reconstruction from medical modalities such as TEE and CT. This role involves applying state-of-the-art machine learning, deep learning, and computer vision techniques to enhance medical image understanding, segmentation, and reconstruction. The candidate will collaborate with cross-functional teams including frontend, backend, QA, DevOps, and clinicians to build AI-driven imaging solutions.

• Develop scalable training and inference pipelines on cloud platforms (AWS preferred; Azure/GCP acceptable).
• Research and implement advanced deep learning architectures including CNNs, GANs, VAEs, and Diffusion Models for medical imaging tasks.
• Collaborate with software engineers to integrate AI components into production-grade imaging applications.
• Work extensively with DICOM data, integrating with PACS systems for data ingestion and retrieval.
• Establishes and promotes a work environment that supports the Quality Policy and Quality System.
• Design, develop, and optimize AI/ML algorithms for medical image analysis, segmentation, and 3D reconstruction from TEE and CT images.
• Demonstrates a primary commitment to patient safety and product quality by maintaining compliance to the Quality Policy and all other documented quality processes and procedures.
• Perform multimodal image registration (CT-CT, CT-MRI, Fluro-Endo, 2D-3D) and develop tools for alignment, calibration, and fusion.
• Stay up-to-date with emerging trends in AI, computer vision, and medical imaging technologies.
• Ensure reproducibility and traceability in experiments using MLOps practices (Docker, MLflow, or similar).
• Document research findings, maintain version-controlled repositories, and contribute to technical publications or IP filings.
• Develop robust 3D reconstruction pipelines from 2D image data and multi-view geometries, tailored to medical imaging workflows.
• Collaborate with teams for dataset curation, labeling, and ground truth generation.
• Enhance and denoise medical images using advanced computer vision and AI-based enhancement techniques.

Requirements

• Expert-level proficiency in Python and deep learning frameworks such as PyTorch and TensorFlow.
• Exposure to regulatory and quality systems in medical device software development (e.g., ISO 13485, IEC 62304).
• Strong software engineering fundamentals — version control (Git), testing, CI/CD, and documentation practices.
• 8+ years of hands-on experience in AI/ML model development with strong exposure to computer vision and imaging applications.
• Experience in 2D and 3D medical imaging (CT, MRI, Ultrasound, TEE) and DICOM data handling.
• Excellent analytical, communication, and collaboration skills with a strong commitment to quality and compliance in healthcare development.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Biomedical Engineering, or related field with focus on AI, ML, or Computer Vision.
• Experience in segmentation, registration, and object tracking within medical image contexts.
• Knowledge of generative and reconstruction models (GANs, VAEs, Diffusion Models) and fine-tuning methods for domain-specific applications.
• Experience in endoscopy imaging, image mosaicing, and fusion with ultrasound imaging.
• Experience with data preprocessing, augmentation, and pipeline automation for large-scale medical datasets.
• Proficiency with classical computer vision techniques (OpenCV, PCL, feature detection, structure-from-motion, SLAM, etc.).
• Experience in 3D visualization, rendering, and medical image annotation tools.
• Strong understanding of 3D geometry, camera calibration, stereo vision, and multi-view reconstruction.
• Familiarity with MLOps, containerization (Docker), and deployment workflows for cloud and edge environments.
• Background in signal processing or physics-based imaging reconstruction methods.
• Knowledge of reinforcement learning or self-supervised learning techniques for imaging applications.
• Experience using cloud platforms (AWS, Azure, or GCP) for model training and large dataset management.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance