Machine Learning Engineer, Application Software
About The Position
Our Application Software team pushes the frontier of model-based autonomous driving, improving core driving performance and developing intelligent features such as personalisation, comfort and collaboration. As a Machine Learning Engineer, you’ll lead critical initiatives to design and deliver ML-driven behaviours that scale from assisted to autonomous driving. Your work will span model architecture, data pipelines, evaluation frameworks and real-world deployment. You’ll work closely with AI Platform, Simulation, Robot Software and Model Release teams to build systems that are performant, adaptable and ready for production, while helping shape the long-term technical direction across Autonomy.
Requirements
- An extensive, proven track record of shipping deep learning systems to production.
- Deep expertise in deep learning, particularly sequential models, control, planning or perception.
- Proficient in Python, experienced with relevant languages such as C++ or CUDA, and confident using ML frameworks, especially PyTorch.
- A strong foundation in software engineering practices and experience building reliable, maintainable ML systems.
- Worked with real-time systems or robotics, ideally including simulation-in-the-loop or vehicle-in-the-loop components.
- Can lead technical initiatives across teams, build alignment and mentor engineers.
Nice To Haves
- Experience in autonomous driving, imitation learning or trajectory prediction.
- Familiarity with personalisation, human behaviour modelling or driver intent inference.
- Experience integrating ML systems into production hardware or multi-agent simulation.
Responsibilities
- Develop and improve end-to-end driving models, advancing their performance, robustness and generalisation.
- Lead technical initiatives in personalised and collaborative driving, including behaviour conditioning, comfort tuning and alignment with user preferences.
- Build evaluation pipelines and metrics to assess open-loop and closed-loop driving performance and product readiness.
- Curate and mine real-world and synthetic data to improve scenario diversity, coverage and feature-specific development.
- Collaborate across engineering teams to integrate models, accelerate iteration and support real-world deployment.
- Mentor senior engineers, drive technical alignment and influence architecture, training and deployment decisions.
Benefits
- Salaries benchmarked against the market annually
- Meaningful equity, sharing in the ownership and long term success of Wayve
- Relocation support and visa sponsorship where applicable
- Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
- Learning and development budgets with support for training, conferences and growth
- Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
