Staff Machine Learning Software Engineer

Join Wayve Science as a Staff Machine Learning Software Engineer. As a founding member of the Multi-Embodiment Generalist Agent (MEGA) team, you will design and build software systems that enable machine learning research for general-purpose robots. Your role will involve creating scalable ML pipelines, data and training infrastructure, and shared tools for researchers. You will work closely with large-scale video and robotics datasets, modern ML frameworks, and increasingly large models. This position offers competitive compensation, private healthcare, paid time off, mental health resources, and opportunities for learning and development.

• Design and build scalable machine learning pipelines for data ingestion, model training, evaluation, and related research workflows.
• Develop and maintain software systems that allow machine learning workloads to scale to larger datasets, larger models, and more experiments.
• Collaborate closely with researchers to understand the requirements of new models and experiments, and translate those requirements into practical software solutions.

• Experience working with large datasets, large models, or other computationally demanding ML workloads
• Experience building and maintaining machine learning pipelines or infrastructure, such as data ingestion, training, evaluation, or experiment workflows
• Strong software engineering skills and experience building high-quality, maintainable software
• 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
• Hands-on experience with modern machine learning frameworks and a good understanding of how ML training and experimentation workflows operate
• Ability to collaborate closely with researchers and engineers and translate research requirements into practical software systems
• Experience designing software systems and abstractions that are reliable, reusable, and able to evolve as requirements change
• We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply
• Experience with distributed training, multi-node systems, or large-scale data processing
• Experience supporting foundation-model training or other large-scale ML research
• Experience with multimodal models, video models, vision-language models, or related ML systems
• Experience working with robotics, embodied AI, simulation, or robot-interaction data
• Experience building infrastructure in a fast-moving applied research environment where requirements evolve rapidly
• Experience improving the performance, reliability, or developer experience of ML training and experimentation systems