Key Notes
Eight or more years delivering platform or infrastructure programmes are required for this full-time, hybrid London role. You will build a small TPM function and directly lead AI Platform initiatives spanning training, compute and on-vehicle inference. Technical understanding of large models, GPUs and embedded deployment is essential; large-scale ML platform experience is desirable.
What You'll Work On
- Lead AI Platform planning and delivery across compute infrastructure, development tools, training technology and embedded inference, managing dependencies and technical trade-offs.
- Build and coach the TPM team while directing major programmes, partnering with engineering leadership to prioritise work and resolve delivery risks.
- Establish programme governance and performance reporting, connecting delivery decisions to developer velocity, compute cost and efficiency, and model training or inference performance.
Why This Role Matters
- Coordinated AI Platform delivery brings compute, training tools and embedded inference dependencies into one programme view, helping Wayve teams sequence the infrastructure needed for model development and deployment.
- Training and embedded inference have different resource constraints, requiring programme decisions that account for compute cost, model performance and the hardware available inside vehicles.
What They Are Looking For
- Experience: Relevant experience includes 8+ years of platform/infrastructure TPM delivery, including people and process leadership.
- Technical: Relevant technical capabilities include ML, GPUs, large-model training and inference, and embedded deployment.
- Technical: Relevant technical capabilities include familiarity with Kubernetes, Ray, Flyte, Docker, Azure and Python, alongside AI-agent proficiency.
- Preferred: Preferred attributes include large-scale ML platforms, autonomy/robotics or engineering experience.