Engineering Manager - Datasets Enrichment

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!

Role Description

We are hiring an Engineering Manager (M4) to lead the team responsible for both semantic enrichment pipelines and the final silver and gold layers of the Wayve Corpus. This team transforms multimodal driving data and perception model outputs into reliable, high quality data products used across autonomy, evaluation, simulation, and research.

The role combines high scale ML in the loop enrichment pipelines such as semantic segmentation, cuboid annotation, embeddings, and BC and ODD signals with production grade data engineering ownership including schema governance, table interfaces, quality gates, lineage, and SLO based operations. You will lead a team of up to 10 engineers across ML engineering, perception, and data engineering.

You will own a multi quarter roadmap that scales enrichment throughput, improves data quality, and hardens corpus tables used across Wayve. You will partner with application, model training, and evaluation, teams to ensure alignment on requirements and interfaces.

This role requires a leader comfortable at the intersection of ML systems and data engineering who can provide clear direction, reliable delivery, and strong people leadership during a period of significant technical and organizational scaling.

Key Responsibilities

• Lead, coach, and grow a team of up to 10 engineers across ML engineering, perception, and data engineering.

• Define team structure, roles, leveling, hiring needs, and long term growth plans.

• Own and scale semantic enrichment pipelines including semantic segmentation, cuboids, embeddings, scenario, and ODD classification.

• Integrate ML assisted labeling, validation, and automated quality checks into enrichment workflows.

• Own the silver and gold layers of the Wayve Corpus including schema evolution, versioning, documentation, lineage, observability, and SLO backed operations.

• Establish data quality gates and quality metrics for enriched and corpus level data.

• Deliver a multi quarter roadmap spanning enrichment and corpus systems with predictable execution.

• Lead architecture decisions to improve efficiency, maintainability, and reliability.

• Partner with Data Platform on distributed compute systems including Spark, Databricks, Ray, and Flyte.

• Align with autonomy, evaluation, and research teams on corpus requirements, interfaces, and lifecycle.

About you

In order to set you up for success as a Engineering Manager - Datasets Enrichment at Wayve, we’re looking for the following skills and experience.

Essential Skills and Experience

• 2+ years managing engineering teams in ML systems, perception, or large scale data infrastructure.

• Experience delivering ML in production or perception pipelines, or strong experience in production data engineering systems. Ideally exposure to both.

• Proven ownership of production data tables such as Delta Lake, Spark, Hive, or BigQuery including schema evolution and multi team consumers.

• Experience with distributed compute systems such as Spark, Databricks, Ray, or Flyte.

• Experience building observable, high throughput pipelines.

• Ability to lead multi quarter delivery, manage dependencies, and align with multiple stakeholders.

• Strong communication and cross functional collaboration skills.

Desirable Skills and Experience

• Experience with multimodal perception data such as images, video, and LiDAR.

• Experience with annotation workflows or ML assisted labeling systems.

• Experience with embeddings, feature stores, or ML data layers.

• Familiarity with data quality frameworks and operational analytics.

• Experience in autonomous vehicles, robotics, or large scale computer vision systems.

This is a full-time role based in our office in London, England, UK. 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. We operate core working hours so you can determine the schedule that works best for you and your team.

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.