Lead Machine Learning Engineer (Computer Vision)

About Motorway

Motorway is the UK’s fastest-growing used car marketplace – our award winning, online-only platform connects private car sellers with over 7,500 verified dealers nationwide, who compete to offer the best price. Founded in 2017, our technology makes the process refreshingly easy, earning us an 'Excellent' Trustpilot rating with over 70,000 reviews. We're not just building a platform; we're changing how people sell cars.
Backed by leading investors like Index Ventures and ICONIQ Growth, and following a successful $190 million funding round, we're on a mission to transform the used car market.
About the role:
We’re looking for an experienced and driven Lead Machine Learning Engineer to lead our Machine Vision team. This role focuses on taking full responsibility for developing, deploying, and maintaining high-quality, performant computer vision models, including classification, object detection, and segmentation production models. Additionally, this role will involve pushing boundaries by building innovative GenAI applications, particularly focusing on API usage and Retrieval Augmented Generation (RAG). You will be joining a team whose mission is to streamline vehicle profiling and transform the online vehicle selling and buying experience for all our customers - including both sellers and dealers.
In this role, you’ll lead the computer vision side, manage and mentor at least one Machine Learning Engineer (MLE), and collaborate closely with machine learning engineers, backend engineers, and product managers to develop scalable, high-performing ML solutions that elevate the customer journey. You’ll combine technical brilliance with strong commercial acumen and understanding ofproduct needs, with pragmatic scalable and robust solutions at the core of your decision making. By applying your expertise in computer vision, leading Gen AI technologies exploration, and team leadership, you'll create cutting edge applications that push the boundary at the interface of AI in the online automotive marketplace.
Key Responsibilities:
Ownership of Motorway’s machine vision capabilities, across a range of models including classification, object detection, and segmentation.

Lead the development, deployment, evaluation, and sustainable maintenance of computer vision models in production environments, ensuring optimal performance, reliability, and scalability.

Develop and implement best practices for MLOps, including version control, CI/CD pipelines, containerisation, and cloud-based orchestration.

Ownership of our image management pipeline including interfacing with third parties to deliver industry standard data quality.

Collaborate cross-functionally: Work closely with data analysts, product managers, and business stakeholders to translate business needs into technical solutions.

Manage and mentor other ML practitioners, sharing knowledge and raising the technical bar across the team.

Lead the innovation! You’ll have a keen passion for staying updated with the rapidly evolving AI landscape, identifying and adopting new techniques, tools, and methodologies as appropriate.

Requirements:
Excellent programming ability in Python and good experience with machine learning libraries such as PyTorch (preferred), TensorFlow, OpenCV etc.

Experience in deploying, maintaining, and optimising deep learning pipelines, focusing on efficiency, performance, and production maturity.

Strong understanding of machine learning principles, deep learning techniques and GenAI concepts such as prompt engineering, chain-of-thought reasoning, prompt chaining, Retrieval-Augmented Generation (RAG), custom-built agents.

Familiarity with LLM and agentic frameworks like LangChain, PydanticAI, or similar.

Proficiency in ML-Ops practices and tools; strong understanding of DevOps and CI/CD.

Experience with cloud platforms, e.g. AWS (preferred), GCP, and deploying models in production.

Experience developing and shipping GenAI solutions utilising Large Language Models (LLMs), with an emphasis on API usage and Retrieval Augmented Generation (RAG).

Proficient in Docker and cloud-based container orchestration services such as AWS Fargate, Google Cloud Run etc.

You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve ambiguity.

You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain.

The ability to align with product requirements, prioritising simpler solutions over ML when appropriate.

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