Machine Learning Engineer - Computer Vision

  • Location
  • London
  • Last Published
  • Dec. 4, 2024
  • Sector
  • Mobility
  • Function
  • Software Engineering

About the role:

We’re looking for an enthusiastic Machine Learning Engineer to join our Machine Vision team. This role focuses on developing high-quality, performant computer vision models and pushing boundaries by building innovative GenAI applications. 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 collaborate closely with machine learning engineers, backend engineers, and product managers to develop scalable, high-performing ML solutions that elevate the customer journey. By applying your expertise in computer vision and exploring advanced Gen AI technologies, you'll create new applications that elevate the process for everyone involved. If you're passionate about innovation in AI and creating impactful solutions, join us to revolutionise the online automotive marketplace.

Key Responsibilities:

  • Contribute to the development, deployment, and 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.
  • Experience in developing and shipping GenAI solutions utilising Large Language Models (LLMs).
  • Collaborate cross-functionally: Work closely with data analysts, product managers, and business stakeholders to translate business needs into technical solutions.
  • You have experience in, and a passion for, mentoring other ML practitioners, sharing knowledge and raising the technical bar across the team.
  • Innovate! You’ll have a keen passion for staying updated with the rapidly evolving machine learning landscape, identifying and adopting new techniques, tools, and methodologies as appropriate.