Manager, Training & Inference Platform

London

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Wayve

Learn how Wayve is leading the way in autonomous driving with their innovative embodied AI technology.

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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

This role is vital as it places you at the core of our organization's capacity to scale and effectively deploy advanced machine learning solutions. Your leadership directly impacts hundreds of ML researchers and engineers by providing seamless access to GPU resources and intelligent scheduling tools that accelerate model training and inference workflows. By building robust, efficient, and reliable platforms, you will significantly enhance productivity, foster innovation, and enable rapid experimentation. 

As the leader shaping our ML infrastructure, your contributions will drive the future direction and success of the company. You’ll oversee two closely-aligned functions:

  1. Training Platform • Maintain and enhance the existing training scheduler (fair-share, preemption, checkpoint/restore).
    • Provide training introspection (W&B integration, MFU metrics) and debug-node tooling for rapid iteration.
  2. Inference Platform
    • Deliver and optimize large-scale GPU inference capacity (persistent & burst).
    • Enhance Flyte-driven smart scheduling, multi-model inference pipelines, and throughput for hundreds of petabytes of labeling workloads.

Your leadership ensures that both training and inference demand from hundreds of ML engineers is met with fast self-serve platform capabilities.

Challenges You Will Own

  1. Team Leadership & Roadmap
    – Grow and mentor the team (will grow to 8+ engineers across both).
    – Define and drive a unified roadmap, balancing near-term demand spikes with long-term platform resilience.
  2. Scheduling & Orchestration
    – Evolve the scheduler with smart-scheduling features across training and inference workloads.
    – Develop advanced analytics and self-service interfaces to empower ML engineers to configure and monitor their inference workloads effectively.
  3. Operational Excellence
    – Implement observability & alerting to maintain 99%+ uptime for both platforms.
    – Improve efficiency of the platform with intelligent scheduling techniques and automatic cancellation of non convergent training jobs.
    – Partner with SRE to automate scaling, failover, and incident response.
  4. Talent Development
    – Recruit and develop platform engineers with a broad range of experience (junior through staff).
    – Foster a culture of ownership, cross-team collaboration, and continuous learning.

About You

Essential:

  • Proven Leadership: Strong experience (8+ years) in software engineering with ≥ 3 years managing SWE platform engineering teams.
  • Technical Expertise: Hands-on with Flyte (or comparable orchestration) and GPU cluster management (e.g., Kubernetes/AKS).
  • Collaboration: Exceptional communication to partner with AI researchers, data platform, and SRE.
  • Talent Development: Track record recruiting, mentoring, and retaining high-performing engineers.
  • Education: BS/MS in Computer Science, Engineering, or related field.
  • Strategic Vision: Strong judgment and vision in defining multi-phase platform roadmaps.

Desirable:

  • Scaling ML Systems: Demonstrated success delivering software to support hundreds of petaflop-hours of training or millions of inference hours.
  • Experience optimizing data locality and multi-region workflows.
  • Familiarity with W&B, MLflow, or similar introspection tooling.
  • Prior work with Flyte or Ray and other large-scale orchestration frameworks.

    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 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.

 

 

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Computer Science Engineering GPU Kubernetes Machine Learning MLFlow ML infrastructure Model inference Model training Pipelines Weights & Biases

Perks/benefits: Career development Flex hours

Region: Europe
Country: United Kingdom

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