Machine Learning Engineer at Winnow

Cluj-Napoca, , Romania -

Full Time

Start Date

Immediate

Expiry Date

08 Jul, 26

Salary

0.0

Posted On

09 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Machine learning, Artificial intelligence, Python, TensorFlow, PyTorch, Deep learning, Computer vision, Object detection, Image classification, Transformer models, Multimodal systems, AWS, Linux, Edge computing, Data annotation, Large language models

Industry

Software Development

Description

About us Food waste is a $1 trillion problem – costing the world over 1% of global GDP. We’re dead set on solving the problem and looking for people to help us achieve our mission. We, at Winnow, believe that food is far too valuable to waste, and that technology can transform the way we produce food. Our team is made of people who all share a passion for food and technology. Winnow was founded in London in 2013 to help the hospitality industry prevent food waste through internet of things tools in the kitchen. We have worked with thousands of sites and are operating in over 90 countries around the world supported by our offices in London, Dubai, Singapore, Cluj-Napoca (Romania) and Chicago. We are a scale-up stage company with a strong base of clients who are rolling out our system globally. We have blue-chip customers including Accor Hotels, IKEA, IHG, Marriott, Compass Group and many others. Winnow’s clients on average reduce waste by over 50% by value and sustain savings. Winnow works with hotels, universities and schools, staff restaurants, event/hospitality kitchens, buffets, pubs, and high street restaurants. Where the system is permanently adopted, pre-consumer waste value is reduced by 50% - 70% with no detrimental impact to the perceived quality or value of the offer to their customers. This represents a typical improvement of food cost savings of 3% to 8%, commonly a 40%+ increase in profitability for operations. As the global leader in addressing food waste, we are committed to continue pushing the envelope on what technology can do to solve this problem. Winnow Vision, our new 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 received tremendous enthusiasm from our clients and the industry. You can read more about it on our website and this article in Forbes. Winnow has recently been ranked #4 in the Global FoodTech 500 for 2025, recognising our position among the world’s leading innovators at the intersection of food, technology, and sustainability. We have also consistently been recognised in the FoodTech 500, the world’s first definitive list of global entrepreneurial talent in this space, further reinforcing our impact in the industry. Other recent accolades include being listed in the 2025 Sunday Times Best Places to Work, a recognition based on feedback from our UK team. While this award is UK-based, 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. Winnow was also named among Impact 50’s most impactful companies to work for. You can read more about it here. We are passionate about living our values and place them at the centre of everything we do. We are excited about like minded talent who share these values, joining us in our mission: Equal parts head and heart. We’re both passionate and measured. We carefully balance the need for quick solutions and pragmatism with the ability to step back, take in the bigger picture and build for the long term. Bravely honest. With each other, that means we’re a transparent organisation where healthy, respectful debate is encouraged. With our customers, we challenge them if we don’t think they’re achieving their goals, whether they be environmental or financial. People of action. Done is better than perfect, and we learn by boldly doing then rapidly improving. We’re breaking new ground, so we know things might go wrong. But we judge ourselves and each other on our reaction and our resilience. Bound by food. We’re a diverse bunch, but our belief in the value of food is the common thread in everything we do. With each other, we celebrate through our love and respect for food. With our customers, it means we work hard to develop creative tools to make it easy for chefs to value food. Hungry and humble. Our product is revolutionary, our people are impressive, and we’re hungry for change. But, we’re just the catalyst for a bigger movement. We stay humble regardless of our success, and make chefs the heroes in this journey. People and planet positive. We’re caretakers of the planet, helping to preserve and support it for now and the future. Our work already minimises the impact that the hospitality industry has on the planet, and we’re also committed to actively reducing our own footprint while doing so. We’re leaving the planet and its people better off than we found them. This is an opportunity to join an exciting organisation and help us propel our growth at what are truly the most exciting and dynamic points in time in our business. You will work alongside a driven team who are motivated by building an exciting business and leaving the world a better place than we found it. 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 experienced Machine Learning Engineer 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. Sponsorship for visa is available for right candidates. About you Minimum Master's degree in Machine Learning, Computer Science, Mathematics, Statistics or equivalent with preferably some commercial experience. Experience in developing and deploying ML and AI models end-to-end gained in at least one corporate environment. Strong knowledge of one or more of the following areas: Object Detection, Image Classification, Action Recognition, Image Generation, or Semantic Segmentation. Experience in Bayesian methods, Reinforcement Learning, Signal Processing or NLP is a plus. Experience with modern deep learning approaches, including transformer-based models and multimodal systems (LLMs/VLMs). Expertise in working with TensorFlow or PyTorch. Experience adapting modern model architectures to solve real-world problems. Familiarity with Linux and AWS. Experience with model inference and optimisation tools (e.g. ONNX, TensorRT or similar). Experience with modern LLM serving frameworks (e.g., vLLM, Ollama) is a plus. Good programming skills using Python. Comfortable working independently, prototyping solutions, and bringing them to production. Teamwork, knowledge transfer, process documentation. Passionate about Machine Learning and Artificial Intelligence. Our technology Technology is at the forefront of what we do, and the success of our company is based on our world-class technology and on finding solutions to real-world problems that have not been solved to date. Our current stack includes: Languages: Node.js, Java, AngularJS, Python, C++, Rust Android apps REST APIs Designing and manufacturing IoT ‘smart’ edge devices and expanding using Linux powered devices on the field collecting data using cutting edge technologies Focus on security, user authentication, permissions, data integrity AWS Cloud using EC2, Redshift, Sagemaker, S3 and other services Agile team using Scrum or Kanban using the Atlassian stack (JIRA, Confluence, BitBucket) Reporting and Analytics using Postgres, Jupyter, Airflow and Grafana Model inference on edge devices via ONNX and TensorRT Model training using TensorFLow and PyTorch Competitive base salary Meal tickets - 40 RON per working day 2 Wellness hours per month plus a 274 RON gross monthly wellness allowance or the option to swap the wellness allowance for a 7Card subscription 25 days of paid vacation time in addition to national holidays, plus the option to buy a further 5 days annual leave Company part-funded private health insurance and eye care allowance Life insurance (3 times base salary) Company stock options package Eligible for discretionary annual bonus Employee Assistance Programme - 24/7 helpline for your wellbeing Learning and development allowance of 1,730 RON annually Hybrid way of working - we’re all in the office on Wednesdays and Thursdays Company provided breakfast & snacks on office days Early Finish Fridays - log off at 3 PM on a Friday if you have completed your tasks by then Our own office space with a great working environment You will love what you do – waking up every day solving one of the biggest social problems of our generation - food waste Committed team members with broad experience who share a common passion to build a world class business

Responsibilities

The Machine Learning Engineer will design and experiment with AI models to detect and recognize food items from images and videos. They will also collaborate with cross-functional teams to deploy these models to edge devices and cloud platforms.