Senior Machine Learning Engineer – Video AI

Meyandy LLC; Deutschland; Hybrid; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

30 vacation days

Flexible working hours

Bike leasing

Company restaurant

Urban Sports Club

Team events

Zusammenfassung

Snke is seeking a Senior Machine Learning – Video AI expert to develop and deploy ML solutions that analyze surgical videos and sensor data. You will collaborate with software developers and ML engineers to build hospital-grade services on the Snke platform, extracting insights for smarter, safer procedures.

You will work across the full ML lifecycle, leveraging AWS/cloud environments and modern tooling to advance AI-based video analysis in the med tech field.

Qualifikationen

• Degree in Computer Science, natural sciences, or similar background with 3+ years in ML and CV.
• Experience with Python and modern ML tooling, experiment management, containers and data version control.

Aufgaben

• Develop and deploy ML apps that analyze video and sensor data from the operating room.
• Collaborate with software engineers and ML engineers to build services on the Snke platform.
• Shape AI-based video solutions for medical use-cases and push innovation in intelligent assistance tools.
• Engage in the full ML lifecycle from data processing to model deployment.

Kenntnisse

Python

Machine learning

Computer vision

Experiment management

Containerization

Orchestration

Data version control

AWS

Ausbildung

Degree in Computer Science or related

Tools

Docker

Kubernetes

ML tooling

Jobbeschreibung

Senior Machine Learning – Video AI at Snke

• You will develop and deploy machine learning applications that analyze video and sensor data from the operating room to improve surgical workflows.
• You will work closely with software developers and ML engineers to build services on the Snke platform that extract meaningful insights and enable smarter, more efficient, and safer surgical procedures.
• In addition, you will leverage modern ML training platforms and strong software engineering skills to drive innovation in intelligent assistance tools and automation.
• Work on learning-based solutions for a variety of tasks in medical data analysis with a particular focus on the processing of surgical videos (e.g. event detection, image segmentation, object detection and more)
• Participate in all phases of the machine learning development life cycle (from requirements engineering and data processing to experimentation, model development/training, and ultimately deployment of solutions)
• Push the limits of intelligent software components for surgical procedure analysis, making use of the ever increasing amounts of video data
• Shape the development and productization of AI based video solutions for medical use-cases
• Contribute to our success with your creative ideas and your independent and self-responsible way of working, ultimately impact the daily work of medical professionals around the world

Requirements

• Degree in Computer Science, natural sciences, or similar background 3+ years of professional experience in using modern machine learning methods along with classic computer vision approaches to solve challenging problems in the area of image processing Experience in state-of-the-art ML tooling related to experiment management, containerization, orchestration, processing pipelines and data version control.
• Profound demonstrated experience in developing complex software systems in Python and/or other programming languages Ideally, you gained this experience during a range of projects in an industrial setting, or you have worked on a PhD in a relevant area.
• Good knowledge in the setup and operation of cloud-based computing environments (ideally AWS) is a plus Experience of working on AI-based products in the med tech industry is a plus

Why Snke

• A supportive, international team connected by shared values and a culture of trust
• Meaningful responsibilities with a lasting impact on global healthtech, improving medical decisions and patient outcomes

Benefits

• 30 vacation days, plus December 24th and December 31st
• Flexible working hours and a hybrid work model within Germany
• Bike leasing via our partner “BikeLeasing” Parking garage and secure underground bike storage
• Subsidized company restaurant and in-house café
• Urban Sports Club membership with employer contribution
• Regular after-work, team, and company events
• Centrally located, modern workspace with a 212 m² rooftop terrace

Contact person Tatjana von Freyberg