Company Description
TOMRA Food is a multinational organisation and a leading provider of sensor-based sorting, peeling and integrated post-harvest solution for the food industries. Transforming global food production to maximise food safety and minimise food loss by making sure Every Resource Counts™, has been our strength for over 50 years.
At TOMRA, we want people to innovate, show passion in their work and be responsible. We encourage the freedom to innovate and take risks that result in breakthroughs that challenge the status quo. We value passion that focuses and commits to meeting success. We believe in a responsible and safe mindset that takes care of our customers, products, and fellow employees.

JOIN THE RESOURCE REVOLUTION!

Job Description
We are looking for a Data Science Architect 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.

System Architecture & MLOps:

• Design DL vision models by selecting a suitable backbone, neck and head and testing the performance of those combinations. Innovations in these areas are highly welcomed.
• Design architecture for real-time deep learning inference on TOMRA sorters, including GPU specifications.
• 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:

• Provide technical leadership and guidance to data scientists.
• Stay up to date of industry trends and emerging technologies to ensure our systems remain cutting-edge.
• Understand customer needs and assist in translating these to technical product requirements.
• Follow latest DL model trends and push improvements to the data science team (this includes making use of new libraries).

Qualifications