Machine learning engineer

Recycleye; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Health insurance

Unlimited holiday

£1,000 professional development budget

Monthly team socials

Direct influence over technical方向

Job summary

Recycleye is hiring to advance our AI-powered waste sorting technology. The role centers on building features, measuring product performance, and collaborating with our data team and field engineers. You will gain hands-on experience with computer vision, edge devices, and real-world deployments.

You will spend time on site, work with cutting-edge robotics, and help shape engineering practices as the team scales. A strong ML/vision background and production-quality Python coding are essential.

Qualifications

• Hands-on computer vision experience with a background in ML, physics, maths, engineering or computer science.
• Around 3-5 years’ experience writing production-quality code, primarily in Python, and promoting good engineering practice.
• Track record of shipping ML into production in a commercial setting, ideally including computer vision on edge devices.
• Solid software engineering fundamentals: tested code, version control and code review.
• Clear communication with both technical and non-technical colleagues, and a collaborative approach.

Responsibilities

• Build new features and improve measurement of product performance.
• Collaborate with the data team and other engineers on client projects.
• Support deployed systems and spend time on site for hands-on validation.
• Contribute to code reviews, testing, and setting engineering direction as the team grows.

Skills

Computer vision

Machine Learning

Python

Software engineering

Communication

Problem solving

Tools

Docker

GitHub Actions

NVIDIA Jetson

GStreamer

Cloud platforms (Azure, AWS, GCP)

Job description

Описание:

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.

Задачи:

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.

Требования:

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. Hands‑on computer vision experience, with a background in ML, physics, maths, engineering or computer science. Around 3-5 years’ experience writing production‑quality code, primarily in Python, and promoting good engineering practice. A track record of shipping ML into production in a commercial setting, ideally including computer vision on edge devices. Solid software engineering fundamentals: tested code, version control and code review. Clear communication with both technical and non‑technical colleagues, and a collaborative approach. Comfort working independently and as part of a small team. Creative, practical problem solving. A love of seeing your work in the real world. You’ll spend time on site and at our demo centre, testing in challenging environments and getting hands‑on with the waste our systems sort. It’s the best way to understand the problem you’re solving.

Будет плюсом:

• computer vision detector‑classifier models (YOLO, RF-DETR)
• segmentation models
• multi‑object tracking
• camera calibration
• homography transforms
• NVIDIA Jetson
• DeepStream / GStreamer
• Docker
• CI/CD (e.g. GitHub Actions)
• cloud platforms (Azure, AWS, GCP, etc.)
• model evaluation and monitoring in production
• Go
• building tools used by other teams
• physical systems or robotics, cameras and lenses
• understanding how technical choices affect customers and the business

Условия:

• Day 1 health insurance through Vitality
• Unlimited holiday
• £1,000 professional development budget per year
• Monthly team socials
• Direct influence over technical direction