Data Science Architect- Computer Vision

Job Description

We are looking for a Data Science Architect (Computer Vision) to lead the design and evolution of our data science systems across machine and cloud platforms. As a key member of the R&D team, you will shape the architecture that powers deep learning inference on TOMRA Food sorters and drive innovation in our cloud-based MLOps platform that was developed to train the models. This role blends technical leadership, system design, and strategic foresight to deliver scalable, high-performance solutions that create real customer value.

Role and Responsibilities :

System Architecture & MLOps :

• Design vision models for real-world food sorting applications
• Design architecture for real-time deep learning inference on TOMRA sorters, including GPU specifications. The tasks include object detection, segmentation and more.
• Design DL vision models (CNN-based like ResNet, MobileNet, EfficientNet & Transformed-based) by selecting a suitable backbone, neck and head and testing the performance of those combinations. Innovations in these areas are highly welcomed.
• Maintain & improve architecture of in-house cloud-based MLOps platform (data science pipelines).
• Design & advise on new features for the MLOps platform.
• Follow latest improvements in AzureML ecosystem and come up with efficiency improvements.
• Optimise model lifecycle process and come up with performance improvements for our DL models in order to create customer value.
• Produce architectural plans for our data science solutions and ensure that these are well communicated and understood by the rest of the data science team.

Technical Leadership :

Qualifications

Essential skills and experience required :

Additional Information

At TOMRA Food, we offer a long-term career. Here’s what you can expect when you become part of our team :

How to Apply :

If this sounds like you, we would love to hear from you! All applications will be managed in the strictest confidence.

TOMRA is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, colour, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristics. Reasonable accommodations will be made and will be provided as requested by candidates taking part in all aspects of the selection process.