Senior Machine Learning Engineer, Search & Index

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!

We are hiring a Senior Machine Learning Engineer for our Search & Indexing team, responsible for making Wayve’s massive corpus of multimodal video data discoverable and searchable. This team builds the indexing infrastructure that powers vector-based and metadata-based retrieval - enabling high-leverage workflows across data curation, training set construction and ML research.

You’ll work closely with the Technical Lead and peers to scale, and evolve the system that supports retrieval across hundreds of thousands of hours of driving data. You’ll contribute to architectural decisions, own complex components, and help define best practices as the team grows.

You’ll play a key role in launching the next version of our indexing stack, supporting basic similarity search and metadata filtering across hundreds of thousands of hours of video and sensor data. The immediate focus is to move quickly: leverage off-the-shelf tools, help inform build vs. buy decisions, and deliver an MVP system in months - not quarters.

This role requires someone who is comfortable in ambiguity, technically pragmatic, and able to make strong architectural decisions in imperfect conditions. You’ll collaborate with ML teams, platform engineers, and downstream users to turn indexing from a bottleneck into a core capability.

• Build and operate production search and indexing systems at billion-vector scale.

• Apply and evaluate embedding models for semantic and multimodal retrieval, including inference, normalization, versioning, and integration.

• Build evaluation frameworks to measure retrieval quality, recall, relevance, filtering accuracy, latency, freshness, scalability, and cost.

• Develop backend services and APIs for vector similarity and metadata-filtered search.

• Own search components from design and implementation through deployment and production operations.

• Collaborate with ML, Data, and Evaluation teams to integrate search into training, curation, and evaluation workflows.

• Support the growth of other engineers through code reviews, technical guidance, knowledge sharing, and mentoring.

In order to set you up for success at Wayve, we’re looking for the following skills and experience:

Essential

• 7+ years of experience in backend, infrastructure, or ML systems, building production systems.

• Experience with vector databases or ANN technologies such as FAISS, LanceDB, or similar open-source solutions.

• Strong understanding of multimodal embeddings and experience evaluating search quality across relevance, recall, filtering accuracy, and