Staff Machine Learning Software Engineer

Sunnyvale, California USAfull timeOn Site

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senior

$311k–$419k

H1B: yes

Wayve The Staff Machine Learning Software Engineer at Wayve designs and builds scalable ML pipelines and software systems to support machine learning research on foundation models for general-purpose robots. This role focuses on infrastructure that enables rapid experimentation and reliable workflows.

Responsibilities

We are looking for an ML Software Engineer to join the Multi-Embodiment Generalist Agent (MEGA) team within Wayve Science as a founding member.
MEGA is building foundation models for general-purpose robots: models that learn from large-scale video, language, and robot-interaction data, then generalize across tasks and embodiments—including mobile manipulators, dual-arm platforms, and humanoids. Our aim is to build agents that can perceive, reason about, and act reliably in the physical world.
Design, build, and maintain scalable ML pipelines for data ingestion, model training, evaluation, and related research workflows.
Build software systems that allow ML workloads to scale to larger datasets, larger models, and more experiments.
Develop clean and reusable interfaces between data, models, training, evaluation, and downstream robotics workflows.
Own and improve the health of the MEGA codebase, including software architecture, testing, reliability, maintainability, and engineering standards.
Identify and resolve performance, reliability, and usability bottlenecks across ML workflows.
Build and maintain infrastructure that supports multiple researchers and ML projects without unnecessarily slowing down iteration.
Work closely with researchers to understand the requirements of new models and experiments, and translate those requirements into practical software solutions.
Build and use distributed training and data-processing pipelines for large models and large multimodal datasets.

Qualification

Experience with software testingExperience working with large datasetsExperience with distributed trainingExperience with multimodal models

Required

In order to set you up for success as an ML Software Engineer at Wayve, we're looking for the following skills and experience.
Strong software engineering skills and experience building high-quality, maintainable software.
Experience building and maintaining machine learning pipelines or infrastructure, such as data ingestion, training, evaluation, or experiment workflows.
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 and a good understanding of how ML training and experimentation workflows operate.
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.
Ability to collaborate closely with researchers and engineers and translate research requirements into practical software systems.
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.