Machine Learning Engineer

The technology stack you will work with includes Linux, NVIDIA DeepStream, NVIDIA Jetson, Docker, Python, C++, GStreamer, PostgresSQL, Timescale DB, AWS Cloud, AWS SageMaker, and NoSQL(DynamoDB).

You will have strong knowledge and understanding of ML/Data Science concepts, processes, statistical modelling, data and model pipelining and ML algorithms. You will also have commercial experience in delivering customer-facing products to the market that utilise computer vision and machine learning.

Ideally, you will also have experience with continuous retraining tools in CI/CD processes for object detection, classification and tracking within computer vision pipelines. You will also be open to learning new technologies, including web technologies, to help integrate AI and data visualisation capabilities into our existing platform.

Essential

• 5+ years of experience working within ML/Data science development
• Experience using NVIDIA DeepStream and Jetson hardware
• Practical experience developing ML pipelines and applications using Python or C++.
• Strong understanding of Linux/Unix shell scripting

Highly Desirable

• Use of Continuous Integration products (Jenkins)
• Use of containerisation technologies Docker Stack / Kubernetes
• AWS and AWS SageMaker experience

This organisation is a long-established leader in smart mobility and intelligent transport solutions, with decades of innovation in traffic data, road safety, and network optimisation. It designs and delivers advanced technologies-from intelligent road-safety products to real-time traffic monitoring and analytics-helping transport operators improve journey safety, reduce congestion, and support more sustainable travel. Its solutions empower customers with actionable insights that enhance how people move across transport networks, contributing to safer, greener and more efficient journeys. Your new role This is a fantastic opportunity to work in a dynamic, cross-functional team with an innovative and forward-thinking approach to problem-solving using modern cloud-native systems to create our products. You will have the opportunity to help shape and guide the development of the product that interacts with various real-world devices throughout the highway network. The platform is built on top of a varied stack that allows it to communicate with real-world IoT devices across the UK and beyond, using multiple AWS services to allow for real-time data capture, feeding a backend service built in Laravel, that provides data to a React.js frontend application. Our new computer vision products are built on the foundations of NVIDIA DeepStream and GStreamer using the NVIDIA Jetson hardware and developed in Python and C++.