Tech Lead, Data Pipeline

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

As the Technical Lead for Data Pipeline Features within our Model Development Platform, you will play a pivotal role in Wayve's mission to revolutionize autonomous driving. Each day, our teams handle and process multiple petabytes of data collected from our fleet of autonomous vehicles and critical partner integrations.

Your technical leadership will directly impact our ability to transform vast amounts of raw data from diverse internal and external sources into structured, actionable insights that power advanced machine learning models and groundbreaking research.

By continuously innovating our data ingestion and processing pipelines, you'll help accelerate the development of safer, more efficient autonomous driving technologies, enabling Wayve to maintain its position at the forefront of machine learning innovation.

Challenges You Will Own

1. Technical Vision & Roadmap:
   
   
• Define and execute a strategic technical roadmap for enhancing and scaling data pipeline capabilities.
  
  
• Drive innovation in pipeline architecture to support dynamic and evolving use-cases.
  
  
2. Pipeline Development & Innovation:
   
   
• Lead the design and implementation of advanced data pipeline features for efficient data ingestion, transformation, and distribution.
• Normalize and unify multiple disparate data sources - including data ingested from external partners - into a consistent and optimized format tailored specifically for AI training and research needs.
• Collaborate closely with robotics, ML engineering, and research teams to continuously enhance pipeline performance and functionality.
  
  
• Develop robust interfaces and systems to reduce bottlenecks and improve reliability and scalability.
  
  
3. Operational Efficiency & Excellence:
   
   
• Establish and maintain best practices for pipeline reliability, including comprehensive observability, alerting, and monitoring systems.
  
  
• Manage initiatives aimed at minimizing pipeline latency, failure recovery, and ensuring compliance with defined service-level agreements (SLAs).
  
  
4. Collaboration & Cross-Functional Integration:
   
   
• Engage actively with cross-functional teams (robotics, ML, data governance) to ensure alignment of technical efforts with overall business goals.
  
  
• Foster a culture of transparency, collaboration, and shared ownership across teams.
  
  
5. Team Development:
   
   
• Mentor and develop engineering talent, promoting professional growth and technical excellence within your team.
  
  
• Contribute to the hiring and onboarding processes to expand the capabilities of the data pipeline engineering team.
  
  

About you

Essential:

• Strong experience (8+ years) in software engineering, specifically focused on developing scalable, complex data pipelines.
  
  
• Proven technical leadership experience in a pipeline engineering or related domain.
  
  
• Expertise in modern data pipeline architectures, including DAG-based orchestration (e.g., Airflow, Flyte).
  
  
• Solid understanding of data engineering practices, distributed processing frameworks, and pipeline optimization techniques.
  
  
• Excellent communication and collaborative skills, capable of working effectively with interdisciplinary teams.
  
  
• Track record of mentorship and talent development.
  
  
• Bachelor's degree or higher in Computer Science, Engineering, or related technical discipline.
  
  

Desirable:

• Experience with robotics or autonomous vehicle sensor data processing pipelines.
  
  
• Familiarity with third-party dataset ingestion and transformation.
  
  
• Understanding of compliance and data governance frameworks (e.g., GDPR, TSAX).
  
  
• Hands-on experience integrating observability and monitoring solutions.
  
  

  This is a full-time role based in our office in London  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 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.