Are you passionate about the intersection of cutting-edge research and healthcare? Do you want to contribute to the development of state-of-the-art solutions that transform patient care in hospitals?

Join our startup and play a key role in our 3D Nutrition Tracker project, leveraging the latest advances in computer vision and deep learning. This project is at the forefront of healthcare innovation, addressing clinical malnutrition and improving patient outcomes across Europe.

For more details about our project and mission, visit alpinasana.ch.

Key Responsibilities

• Robust Computer Vision in Clinical Environments

Improve the accuracy, robustness, and performance of computer vision models operating on RGB-D data in real hospital settings.

• Data-Efficient Hospital Onboarding and Continuous Learning

Engineer automated data selection and model update workflows to minimize manual labeling effort when onboarding new hospitals.

• Engineering 3D Vision and Food Amount Estimation

Implement scalable pipelines for depth processing, 3D reconstruction, and synthetic data generation, including simulated food scenes, occlusions, and controlled variations, to accelerate research on food amount estimation.

Requirements

• Education

Master’s degree or equivalent practical experience in Computer Vision, Computer Science, Robotics, or a related field. A PhD is a plus but not required.

• Computer Vision and ML Engineering

Strong hands-on experience building, optimizing, and maintaining deep-learning-based computer vision systems, particularly for instance segmentation, depth-based perception, or related tasks.

• Cloud and Deployment Environments

Familiarity with cloud platforms such as AWS, Azure, or GCP and containerized environments including Docker and Kubernetes.

• Software Engineering

Proficiency in Python and PyTorch with solid software engineering practices such as modular code design, testing, version control, and code reviews, as well as experience maintaining production ML codebases.

• MLOps and Production Pipelines

Hands-on experience with ML operations including experiment tracking, reproducible training, automated training and inference pipelines, model versioning, and monitoring in production environments.

• Applied and Proactive Problem-Solving Mindset

A proactive, hands-on approach to identifying bottlenecks and improvement opportunities, with the ability to translate evolving research ideas and own proposals into stable, scalable, and maintainable production systems in a fast-moving startup environment.

Nice to Have

• 3D Data and Geometry Processing

Practical experience working with RGB-D data, depth images, point clouds, and fundamental 3D geometry concepts such as projections, calibration, reconstruction, and mesh or point cloud processing.

• Data-Centric Machine Learning and Labeling Workflows

Experience handling large-scale datasets, annotation workflows, and data-efficient learning setups such as active learning, uncertainty-based sampling, or dataset curation.

• Generative Models for 3D Data

Exposure to modern generative approaches for 3D or image synthesis, including diffusion-based models or NeRFs.

• Domain Interest

Interest in applied healthcare technology and nutrition tracking in real-world clinical settings.

Why Join Us

• Competitive Compensation

We offer a competitive salary and stock options to reward your expertise and contributions.

• Flexible Working Arrangements

We provide flexibility in both schedule and work location, allowing you to tailor your working style to your needs.

• Be Part of a Startup

Join an innovative startup and play a leading role in a project at the cutting edge of healthcare technology, with significant opportunities for growth and impact.

How to Apply

To apply or for more information, please send your CV to [email protected].

Best regards,

Raban Iten on behalf of the ALPINA+SANA Team