Machine Learning Engineer

We are hiring a Machine Learning Engineer to lead development and deployment of our endoscopic image analysis systems. This role owns the full ML lifecycle-from data strategy through production deployment-and contributes directly to how our devices interpret and interact with the physical world.

You will work on computer vision models for gastric imagery, image enhancement under constrained in vivo conditions, and perception systems supporting navigation and localization. You will collaborate closely with hardware, firmware, and simulation teams to integrate ML into a real-world medical device system.

This is a mid-level role with significant ownership and the opportunity to mentor junior contributors.

What You Will Do

• Own the end-to-end ML pipeline: data curation, model development, evaluation, deployment, and monitoring

• Design, train, and validate computer vision models using frameworks such as PyTorch

• Develop image enhancement pipelines

• Optimize models for performance across accuracy, latency, and compute constraints

• Implement neural compression techniques

• Build and maintain dataset infrastructure

• Deploy models into production environments with CI/CD and monitoring

• Contribute to localization and pose estimation

Do you have experience in System deployment?, 4+ years of ML engineering experience or equivalent

• Experience deploying production computer vision models

• Strong foundation in deep learning

• Proficiency in Python and PyTorch

• Experience with MLOps tools

• Strong software engineering fundamentals

• Strong communication skills

• Experience in image enhancement, compression, or perception systems

Nice to Have

• Medical imaging experience (e.g., DICOM)

• C# or Unity familiarity

• SLAM or localization experience

• Robotics or autonomous systems experience, * Proficiency in Python and PyTorch: 2 years (Required)

• Deep learning: 1 year (Required)
• MLOps tools: 1 year (Required)
• image enhancement, compression, or perception systems: 1 year (Required)
• Machine Learning engineering: 4 years (Required)
• deploying production computer vision models: 3 years (Required)

Endiatx is a medical device company developing microrobotic systems for diagnostic use inside the human body. Our flagship platform, PillBot , is a propeller-driven endoscopic capsule designed to enable real-time visualization of the stomach without traditional endoscopy.