Senior Machine Learning Engineer, Search & Index

Wayve

$311K — $350K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years in backend, infrastructure, or ML systems, building production systems.
  • Experience with vector databases or ANN technologies like FAISS, LanceDB.
  • Strong understanding of multimodal embeddings and evaluation of search quality metrics.
  • Proficient in Python or other systems languages.
  • History of building search services, APIs, and large-scale indexing pipelines.
  • Proven ability to deliver MVP systems in ambiguous environments.
  • Ability to work across different system domains (infra, ML, data curation).

Responsibilities

  • Build and operate production search and indexing systems at billion-vector scale.
  • Evaluate embedding models for semantic and multimodal retrieval.
  • Create frameworks to measure retrieval quality and performance metrics.
  • Develop backend services and APIs for vector similarity search.
  • Own the design, implementation, and deployment of search components.
  • Collaborate with cross-functional teams to integrate search into workflows.
  • Mentor and guide other engineers through code reviews and knowledge sharing.

Benefits

  • Full-time role based in Sunnyvale, CA with a hybrid work model.
  • Competitive equity package offered.
Full Job Description
The role

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.
Key Responsibilities
  • 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.
About you

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 performance.
  • Strong coding skills in Python or other systems languages
  • Experience building search services, APIs, and large-scale ingestion and indexing pipelines.
  • Experience delivering 01 systems in ambiguous or exploratory problem spaces.
  • Comfortable working across system boundaries (infra, ML, data curation)
Desirable
  • Experience with large-scale ML pipelines or distributed data infrastructure.
  • Familiarity with multimodal data, including video, images, sensor data, and metadata.
  • Exposure to active learning, semantic retrieval, or training-data selection workflows.
  • Prior experience in autonomy, robotics, or large-scale data infrastructure
  • Experience evaluating technical vendors and working with external technology providers.

#LI-HH1

This role is a full-time role based in Sunnyvale, CA (hybrid) and the reasonably estimated salary for this role ranges from $311,850 to $350,625, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.

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