At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.

Make Wayve the experience that defines your career!

The role This is a rare opportunity to join the small but high-leverage engineering team powering Wayve’s foundation model—at the heart of our end-to-end autonomous driving. Embedded within the Science group, you’ll build the infrastructure that enables researchers to iterate faster, train at scale, and ship smarter models. If you thrive at the intersection of research and engineering, and love building systems that accelerate discovery, this is your chance to make a defining impact on one of the most ambitious AI challenges in the world.

Key Responsibilities

• Design and scale infrastructure for data ingestion, filtering, and curation of multi-modal embodied data
• Build robust, efficient training, evaluation, and inference pipelines to support foundation model development
• Partner closely with scientists and MLEs to accelerate experimentation and unblock research
• Improve ML systems performance, scalability, and automation across the stack
• Act as a cross-functional force multiplier—connecting Science, Software, and Data teams through well-designed tooling and systems

About you In order to set you up for success as a Software Engineer at Wayve, we’re looking for the following skills and experience.

Essential

• Strong software engineering skills with experience building and maintaining distributed systems, data pipelines, or backend platforms at scale.
• Experience developing infrastructure that supports machine learning workflows—such as training orchestration, evaluation tooling, or inference systems
• Comfort working closely with research or ML teams to understand their iteration needs and build systems that accelerate them.
• Familiarity with technologies like Flyte, Ray, Spark, Airflow, or Kubernetes, and an understanding of how to use them to scale data and compute.
• Ownership mindset with the ability to identify bottlenecks, operate across team boundaries, and “get stuff done” in ambiguous, fast-moving environments.

Desirable

• Experience working with large-scale multi-modal datasets (e.g. video, LiDAR, radar, language) and designing systems for ingestion and filtering.
• Prior experience in a foundation model or autonomy-focused team, especially in an infrastructure or ML platform role.
• Contributions to open-source ML or infra projects (e.g. Flyte, Ray, Dask, MLFlow) or experience with evaluation tooling at scale.
• Demonstrated technical leadership—whether through driving cross-functional projects, mentoring others, or setting architectural direction

This is a full-time role based in our office in Vancouver. At Wayve we want the best of all worlds so we operate a 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.

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know

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.

For more information visit Careers at Wayve.

To learn more about what drives us, visit Values at Wayve

DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.