Machine Learning Engineer, Av Engineering

Wayve Wayve · Robotics · Herzliya, Israel · AV Engineering

Machine Learning Engineer at Wayve focused on building and shipping end-to-end driving models for Level 2 to Level 4 autonomous driving systems. The role involves owning the full ML lifecycle from data curation and training to evaluation and on-road validation, with a strong emphasis on product delivery and real-world outcomes.

What you'd actually do

  1. Develop the AI driver model architecture and training algorithms to introduce and enhance the safety behaviors for L2/L3/L4
  2. Own key parts of the training model lifecycle, including evaluation strategy, success metrics, and iteration planning.
  3. Mine, bucket, and curate real-world and synthetic data to teach specific driving behaviours, and implement data schemes to support training.
  4. Run and analyse on-road and offline experiments, translate results into clear next steps, and drive improvements through repeated training cycles.

Skills

Required

  • deep learning model training
  • end-to-end ML ownership
  • production ML deployment
  • real-world constraints
  • quality and safety requirements

Nice to have

  • Reinforcement learning
  • end-to-end driving models
  • transformer networks
  • Automotive or OEM experience
  • deploying ML into safety-critical systems
  • Pytorch lightning training infrastructure

What the JD emphasized

  • Proven experience training deep learning models, with clear end-to-end ownership (data, training, evaluation, iteration)
  • Proven Experience taking ML models into production, including working through real-world constraints and quality and safety requirements

Other signals

  • end-to-end driving models
  • shipping models into the car
  • direct impact on high-priority commercial deliveries
  • train and iterate on end-to-end driving models
  • own the full loop from data and training through evaluation and on-road validation