W

Wayve

End-to-end autonomous-driving software for vehicles

Lead Technical Program Manager - AI Platform

Program ManagementUpdated on Nov 9
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • At least 8 years of hands-on technical programme management experience across platform, infrastructure, compute, machine learning infrastructure, developer tooling, training, or inference systems.
  • Experience building or scaling a programme function, leading people and processes, and delivering outcomes with ownership.
  • Ability to build, coach, and grow high-performing teams, hire to strengthen the team, and raise the technical programme management standard.
  • Strong technical depth across machine learning infrastructure, compute, and embedded systems, with the ability to engage credibly with platform and systems engineers without writing production code.
  • Strong understanding of machine learning, graphics processing units, and model training and inference for models from 500 million to over 20 billion parameters, including supporting compute and orchestration.
  • Embedded or on-vehicle systems experience, including inference optimisation, deploying models to constrained edge compute, and hardware-software trade-offs.
  • Familiarity with compute management, machine learning platform tooling, and model-development or experiment workflows using technologies such as Kubernetes, Ray, Flyte, Docker, Azure, and Python.
  • Proficiency with artificial intelligence agents and coding assistants such as Cursor, Claude, or Codex.
  • Ability to remain objective under pressure and adapt in ambiguous, fast-moving environments, bringing structure without unnecessary process.
  • Systems thinking, including understanding how components of a complex platform stack interact and how changes affect other components.
  • Product-minded approach that focuses on programme users, prioritises by impact, and defines outcomes rather than merely tracking activity.
  • Ability to align and influence machine learning, research, infrastructure, embedded, and engineering teams without relying on formal authority.
  • Ability to connect technical investment to measurable outcomes, including developer velocity, compute efficiency, cost, and model performance, and communicate progress using appropriate metrics.
  • Openness to feedback and continuous improvement of personal and team practices.

Responsibilities

  • Build, coach, and support a small technical programme management team, developing team members, helping them work through challenges, and raising delivery standards.
  • Partner with AI Platform and Engineering leadership to align priorities, challenge trade-offs, and hold teams accountable for outcomes.
  • Coordinate across machine learning and research, infrastructure, embedded and on-vehicle engineering teams, cloud partners, and vendors to manage dependencies, surface risks, and remove blockers.
  • Use key performance indicators, dashboards, and operational reviews to track delivery, identify bottlenecks, and inform decisions.
  • Represent AI Platform in company-level reviews, clearly communicating progress, risks, and decisions and connecting delivery to business impact.
  • Build and scale the technical programme management function for AI Platform, hiring to fill capability gaps and growing a high-performing team.
  • Own planning, prioritisation, and execution across the AI Platform roadmap in partnership with engineering leadership.
  • Lead programmes across data and compute infrastructure, developer tooling, training technology, compute management, model-development workflows, and embedded and inference optimisation.
  • Establish scalable planning cadences, governance, escalation paths, and operational practices that provide structure without slowing delivery.
  • Drive measurable improvements in developer velocity, compute efficiency and cost, training and inference performance, and platform reliability.
  • Help engineering leaders deliver high-leverage outcomes by balancing technical trade-offs and ensuring commitments result in impact.

Desired Qualifications

  • Experience with a large-scale machine learning or compute platform used by hundreds of engineers and researchers.
  • Experience with embedded or edge inference, on-device model optimisation, hardware-aware machine learning, autonomous vehicles, robotics, or another large-scale machine learning and infrastructure environment.
  • An engineering or computer science degree, or experience working as an engineer.

About the Company

Wayve

End-to-end autonomous-driving software for vehicles

Wayve provides end-to-end autonomous-driving software for automakers and fleets that runs entirely on onboard compute and sensors, without relying on HD maps or city-by-city engineering. The system uses foundation models capable of zero-shot driving and has demonstrated ability to drive across 500+ cities in Europe, North America, and Japan. Unlike traditional AV stacks that depend on mapped data and per-city customization, Wayve aims to generalize driving with its onboard AI across diverse environments. Its goal is to scale commercial robotaxi trials from 2026 and bring supervised autonomy to consumer vehicles from 2027, backed by substantial funding partnerships to support rapid deployment.

Company size
1,001-5,000
Company stage
Series D
Total funding
$2.6B
Headquarters
London, United Kingdom
Founded
2017

Recently Posted Jobs

Explore more opportunities at Wayve

See more jobs