Machine Learning Scientist

About Winnow

Winnow is developing cutting edge technology to tackle the $1 trillion global food waste problem by transforming the way we produce food.

Established in 2013, we are currently operating in over 70 countries, and we are just at the start of our journey.

As the global leader in addressing food waste, we are committed to continuing to push the envelope on what technology can do to solve this problem. For example, Winnow Vision, our artificial intelligence-based technology, is trained to automatically track all food waste thrown away. It has won awards at the World Economic Forum and has been received tremendous enthusiasm from our clients and the industry. You can read more about it on our website. 

Other recent accolades saw Winnow listed in the 2025  Sunday Times Best Places to Work - a recognition based on feedback from our UK team. While this award is based in the UK, it reflects something global: a culture built on purpose, collaboration, and the belief that businesses can - and should - tackle real-world problems while being great places to work. 

At Winnow, technology is more than code, it is a force for environmental change. If you want to apply your coding skills to solve real-world problems and contribute to a more sustainable future, we would love to hear from you.

About the team

Our Machine Learning Research team develops cutting-edge solutions to some of the world’s most complex large-scale food recognition problems. Our models have not only surpassed human-level performance, but in some areas have exceeded human expectations, enabling new possibilities in food recognition and waste reduction.

The team’s work spans the entire lifecycle of machine learning research and application, from cutting-edge research to real-world deployment. By combining rigorous experimentation, deep technical expertise, and close collaboration with other Winnow teams, our Machine Learning Research team ensures that Winnow continues to lead the way in applying AI to tackle food waste at scale.

About the role

Reporting to the Head of Research Science, we are looking for an Machine Learning Scientist to join the team. Key responsibilities include:

• Designs tests and experiments to build machine-learning and AI models for detecting and recognising food and non-food items from images and videos and optionally texts, not excluding other contextual data like date, time, season, geography etc to improve the performance of the models.
• Maintains a high level of data quality via directing and guiding the annotation team and third-parties in data annotation and labelling, including leveraging modern AI-assisted annotation approaches.
• Manages the data efficiently for model training and evaluation.
• Applies state-of-the-art model architectures and techniques (including deep learning, transformer-based and multimodal models) to improve the models.
• Prepares reports and presents results to summarise main findings and conclusions
• Presents results of scientific research to stakeholders and may contribute to external publications or technical articles.
• Writes software and algorithms for training and running the models within Winnow applications.
• Collaborates with other teams at Winnow in deploying the models to Winnow's applications to embedded systems like NVIDIA Jetson devices and to the cloud platforms such as AWS and GCP.
• Explores and integrates Large Language Models (LLMs) and Vision-Language Models (VLMs) for tasks such as annotation support, detection, multimodal reasoning, and building AI-powered services and agents.