Wayve-posted 1 day ago
Full-time • Mid Level
Hybrid • Sunnyvale, CA
501-1,000 employees

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. About us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. 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.

  • 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
  • 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.
  • 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
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