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Recycleye in the United Kingdom is seeking a hands-on ML/CV engineer to build features for waste sorting products deployed on real lines. You will work across model architectures, calibration, and end-to-end performance in production.
You’ll collaborate with data and plant monitoring teams, deploy on NVIDIA Jetson devices, and spend time on site at demo centres and customer sites. The role requires 3–5 years of Python production experience and strong software engineering fundamentals.
At Recycleye we are revolutionising recycling. Our ground-breaking AI-powered robots and optical sorters are making waste sorting faster, cleaner and more profitable. With our advanced tech, the previously unsortable can now be sorted efficiently and effectively. Founded in 2019, we have grown rapidly ever since, with installations at leading waste management companies across Europe and the US.
We are on a mission to help our clients produce higher quality outputs – turning the world’s waste into valuable resource. And our work has never been needed more. Worldwide only 9% of plastic waste is being recycled – every day, we are proud to work on making a meaningful difference towards a sustainable future.
Why choose to work at Recycleye? Our team works together to grow and succeed, driven by our shared values of ambition, curiosity, customer centricity, integrity and respectful ideation. We offer great benefits, built-in upskilling and unlimited holiday.
We know that our mission will be achieved by having the most passionate, driven, talented, and all-around best people on our team. So come and help us shape the future!
Our team develops new features across Recycleye’s waste sorting and plant monitoring products, improving the end-to-end performance of our systems. That might mean evaluating and deploying new model architectures, adapting ideas from ML papers to our use cases, implementing novel object tracking algorithms, diving deep into camera optics and calibration, or making our DeepStream pipelines more efficient. Everything we build runs in production on real sorting lines, so we look for the solution that works best for the problem, which might mean stepping back and choosing a better camera rather than chasing a cool new model.
You will be a core member of a small, high-impact ML R&D team. Building new features and developing better ways to measure how well our products perform, whether that’s sorting a waste stream or understanding what’s in it, and how real site conditions affect that performance. You will work closely with our data team, who train models day to day for client projects and rely on the tools we build, and with colleagues developing a new plant monitoring product. You will also help support our deployed systems and spend time on site, getting hands-on with the waste they sort.
As the team develops, you will help shape how we work, from code review to testing, and take on more responsibility for planning and decision-making. Along the way you will build a deep understanding of our products and the waste sorting industry, keep up with advances in computer vision, and share what we learn across the company.
We work mostly in Python, with some Go, deploying models and algorithms to NVIDIA Jetson devices running DeepStream pipelines, supported by Docker, GitHub Actions and Azure.
We’re looking for someone who is proactive, driven and practical, comfortable with change, and keen to learn. We don't expect you to be an expert in everything on day one.
We don't expect you to have all of these, and we’ll help you build the rest:
Travel: Occasional to Europe or US