Description
We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future.
You will design and build the software systems that enable MEGA's machine learning research. This includes scalable ML pipelines, data and training infrastructure, and the shared tools and abstractions that allow researchers to move quickly from an idea to a reliable experiment.
Responsibilities:
- Design and maintain scalable pipelines for data ingestion, model training, evaluation, and experimentation.
- Build reusable interfaces and shared tooling across data, models, training, evaluation, and downstream robotics workflows.
- Partner with researchers to translate evolving model and experiment needs into practical software systems.
- Diagnose and resolve performance, reliability, and usability bottlenecks across large-scale ML workloads.
- Raise the quality of the shared codebase through strong architecture, testing, documentation, and engineering standards.
- Support distributed training and data processing across large video, language, and robot-interaction datasets.
Requirements:
- Strong software engineering skills and experience building high-quality, maintainable software.
- Experience building and maintaining machine learning pipelines or infrastructure.
- Experience designing software systems and abstractions that are reliable, reusable, and able to evolve as requirements change.
- Hands-on experience with modern machine learning frameworks.
- Strong debugging skills and the ability to investigate problems across complex ML systems.
- Experience with software testing, code quality, and engineering practices for maintaining a healthy shared codebase.
- Experience working with large datasets, large models, or other computationally demanding ML workloads.
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