Senior Machine Learning Engineer, AV Core

📋 Job Overview

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.

🏢 About Wayve

Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

Our ambition is to make autonomy universal. Wayve’s mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

🎯 The Role

🧠 Your day-to-day
You’ll lead large-scale data enrichment and curation initiatives, collaborating across pre- and mid-training, reward modelling, self-supervised labelling, and the Data Enrichment Platform. You’ll develop workflows for mining hard and rare events, investigate how models perform in the real world, and improve the efficiency and reliability of our machine learning operations stack.

✅ Key Responsibilities

• Lead on large-scale data enrichment within the Core Model Safety team, including collaborations with Pre/Midtraining, reward modelling, self-supervised labelling, and the Data Enrichment Platform.
• Build workflows for large-scale enrichment, data curation, and hard/rare event mining in support of robust model performance and introspection.
• Design and train out-of-distribution detection mechanisms to enable robust driverless operation.
• Work at the intersection of model engineering, infrastructure, compute, and data, shaping the boundaries and architecture across those teams.
• Use your judgement and expertise to improve the overall efficiency of the machine learning and operations stack.

🙌 You should apply if

📌 Required Qualifications

• Hands-on experience with ML systems deployed in the real world.
• Proficiency in Python and PyTorch, with strong software engineering practices and hands-on experience building reliable machine learning training and evaluation systems.
• A strong track record with ML operations and infrastructure, including experience with distributed computing environments and large-scale inference.
• Senior-level ownership and collaboration: able to lead a substantial technical area, work across research and engineering boundaries, and bring others along through clear written and verbal communication.

⭐ Desirable Experience

• Prior experience in autonomous vehicles or robotics with hands-on deployment and closed-loop validation on physical systems.
• Experience mining, generating, or evaluating rare events using simulation and fleet or heterogeneous real-world data.
• Experience setting up cloud-based monitoring solutions for large-scale operations, including dashboards, logging, and real-time alerts.
• Experience with transformer-based and multimodal architectures, including vision-language models (VLM), vision-language-action models (VLA), or equivalent.
• Proficiency in C++, CUDA, distributed training, or performance optimization for production machine learning systems.

🎁 Benefits

What’s in it for you (Location dependant):
💰 Salaries benchmarked against the market annually
📈 Meaningful equity, sharing in the ownership and long term success of Wayve
✈️ Relocation support and visa sponsorship where applicable

🛂 Visa & Eligibility

Relocation support and visa sponsorship where applicable