Wayve is looking to scale end-to-end neural networks for autonomous driving and needs a Machine Learning Engineer to help achieve this goal.
Requirements
- 7+ years of software and machine learning engineering experience in an industrial or applied research environment
- Good insight into the practical aspects of training, validation, testing and metrics for deep learning features/models
- 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
- Good grasp of machine learning literature, ideally published
- Comfortable working with large quantities of image and video data
- BSc above in Machine Learning, Computer Science, Engineering, or a related technical discipline or equivalent experience
Responsibilities
- Developing and implementing machine learning models and robotics systems to enhance the capabilities of our Autonomous Vehicle stack
- Collaborating with cross-functional teams to contribute to the broader company strategy and roadmap, focusing on machine learning applications
- Enhancing skills and knowledge in machine learning through continuous learning and application, while contributing to the growth and mentorship of junior engineers
- Evaluating project decisions and outcomes, identifying dependencies, and analyzing risks associated with machine learning deployments
- Troubleshooting and optimizing machine learning models and systems - identify potential issues, challenge existing assumptions, introduce innovative solutions, and implement feedback loops to enhance model performance
- Technical leadership of at least one company wide program
- Allocating personal bandwidth and technical resources effectively to meet both project requirements and personal professional development needs
Other
- Passion to work in a team on research ideas that have real product impact
- A culture that is ego-free, respectful and welcoming
- Hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home
- Core working hours so you can be where you need to be for family and loved ones too
- Benefits such as an onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
