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Machine Learning Engineer

Experienced Machine Learning Engineer to scale end-to-end neural networks.
Wayve
Hybrid
On-Site
United Kingdom
Undisclosed salary
Job Description

Wayve is seeking a Machine Learning Engineer to join their Embodied AI division in London. The ideal candidate will help scale end-to-end neural networks for autonomous driving, working with modelling, robotics, data, and detectives teams. This role involves technical leadership, collaboration, and continuous learning to enhance Wayve's autonomous vehicle stack.

Role Involves:

  • Technical leadership of company-wide programs
  • Developing and implementing machine learning models and robotics systems
  • Collaborating with cross-functional teams on company strategy
  • Enhancing skills and knowledge in machine learning
  • Allocating resources effectively for project and personal development
  • Fostering a collaborative and innovative work environment
  • Evaluating project decisions and outcomes, identifying dependencies, and analysing risks
  • Troubleshooting and optimising machine learning models and systems

Requirements:

  • 7+ years of software and machine learning engineering experience
  • Good insight into training, validation, testing, and metrics for deep learning
  • Passion for teamwork and real product impact
  • Good grasp of machine learning literature
  • Comfortable working with large quantities of image and video data
  • BSc in Machine Learning, Computer Science, Engineering, or related field
  • Strong software engineering experience in Python and other relevant languages (e.g. C++ and CUDA)
  • Direct experience working in at least one of computer vision, robotics, simulation, graphics, or large language models.
  • MS, or above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience

What Wayve Offers:

  • Opportunity to shape the future of autonomous driving
  • Competitive compensation and benefits
  • Dynamic and fast-paced work environment
  • Ego-free, respectful, and welcoming culture
  • Onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
  • Hybrid working policy
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