Wayve-posted 8 days ago
Full-time • Manager
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 We are hiring an Engineering Manager to lead our new Indexing Team in Sunnyvale. This team owns the infrastructure and systems that make Wayve’s vast video corpus discoverable and searchable — powering downstream workflows across data mining, model training, and evaluation. This role will be responsible for scaling our indexing stack to support vector-based, semantic, and metadata-based search over hundreds of thousands of hours of multimodal video data. The indexing system underpins core ML and curation efforts across Wayve’s autonomy stack and foundation model research. You will initially hire and manage a team of 4 engineers and play a key role in defining technical direction, delivery rituals, and long-term org design. As the demand for index-driven workflows grows, you’ll be responsible for growing the team further in 2026, building a world-class capability around video corpus discovery and retrieval.

  • Lead and grow a team focused on the design, scaling, and reliability of Wayve’s corpus indexing systems.
  • Define the technical architecture for: Embedding-based retrieval (e.g., CLIP, internal latent spaces) Metadata-based querying across large-scale video + sensor datasets Multi-modal index structures for fast, expressive search
  • Establish engineering rituals (planning, standups, retros) and team delivery rhythm.
  • Work closely with ML, data curation, and simulation teams to align indexing priorities with downstream workflows.
  • Ensure the indexing system meets evolving performance, recall/precision, and observability needs at scale.
  • Drive hiring, onboarding, and team structure planning to support 2026+ growth.
  • Collaborate with platform and infra teams to ensure efficient data access, durability, and integration with pipeline backends.
  • 2+ years experience leading high-performing engineering teams.
  • Proven track record designing and scaling distributed systems, particularly search or indexing infrastructure.
  • Experience with vector similarity search, ANN algorithms, or semantic retrieval systems.
  • Strong technical fluency with Python and/or systems-level languages (e.g., C++, Go); familiarity with data stack components like Spark, Ray, Databricks.
  • Comfort working with ML workflows or embedding-based pipelines.
  • Demonstrated ability to grow teams, drive team rituals, and lead through ambiguity.
  • Experience with modern vector search frameworks (e.g., Faiss, Weaviate, Pinecone, Vespa).
  • Familiarity with multimodal indexing (video + sensor + metadata).
  • Background in ML platform engineering or data discovery systems.
  • Prior exposure to autonomous vehicles, simulation systems, or robotics data flows.
  • Understanding of active learning, dataset mining, or data curation.
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