ADAS Feature Engineer, Application Software

Before the detail, here's the challenge you'd help us solve. We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that. Here’s what this particular role covers. About our Engineering Teams🛠️ AI Platform builds the platform the whole company builds on: the data and compute infrastructure, model-development workflow tooling, training technology, compute management, and embedded / inference optimisation that get Wayve’s models trained, iterated and deployed onto the vehicle. The systems this team delivers determine how fast Wayve can develop and ship models, how efficiently we use compute, and how well our models perform in training and on the vehicle. Your day-to-day🧠 As the Lead Technical Program Manager for AI Platform, you’ll build and lead the technical program management function for the organisation. You’ll be the delivery partner to engineering leadership, driving predictable, high-leverage delivery across the platform roadmap. You’ll lead flagship programs directly while supporting and coaching a small, high-impact TPM team. Your impact will be measured in developer velocity, compute efficiency and cost, training and inference performance, and the reliability of platform delivery. A successful TPM leader is a force multiplier—helping teams move faster, more effectively and with purpose. What you’ll be working on:🧩  Building and leading the function: Build, coach and grow a small TPM team, hiring to fill gaps and raising the bar for technical program management.  Owning platform delivery: Partner with AI Platform leadership on planning, prioritisation and execution across data and compute infrastructure, developer tooling, training technology, compute management, and embedded / inference optimisation.  Being a trusted partner to engineering leadership: Operate as a leader within the organisation, helping engineering leaders deliver high-leverage outcomes and holding them accountable for commitments and impact.  Driving flagship programs directly: Lead complex programs across the platform stack, from infrastructure and model-development workflows to training systems and on-vehicle inference. 2  Establishing scalable practices: Develop planning cadences, governance, KPIs, dashboards, escalation mechanisms and operational reviews that bring structure without slowing delivery.  Aligning teams and partners: Work across ML / research, infrastructure, embedded / on- vehicle and engineering teams, alongside cloud and vendor partners, to manage dependencies, risks and trade-offs.  Connecting delivery to outcomes: Tie platform delivery to developer velocity, compute efficiency and cost, and training / inference performance, representing AI Platform in company- level reviews. You should apply if:🙌 Essential  You bring 8+ years of platform / infrastructure program experience. You’ve