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Technical Director, Model Engineering

Sunnyvale, California USA

AI engineering

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

You will lead the technical direction of Wayve’s Embodied AI Platform.

This is a senior individual contributor role focused on technical leadership, not people management. You’ll operate at the intersection of research and engineering, shaping how we build, train, and scale foundation models for real-world autonomy.

Your focus is turning cutting-edge science into scalable, production-ready systems. That means defining how we train large models efficiently, extract maximum value from data, and scale compute and infrastructure in a cost-effective way.

You’ll play a key role in driving Wayve’s “core” embodied AI model—setting the technical direction for data, training, and evaluation systems that support rapid iteration and reliable deployment.

Key responsibilities

• Define the technical vision for Wayve’s embodied AI platform, balancing fast experimentation with scalable, reliable systems.
• Bridge research and production by integrating new scientific advances into training pipelines and downstream autonomy systems.
• Drive strategy for large-scale model training, evaluation, and performance optimisation.
• Shape Wayve’s approach to data and compute at scale, including data selection, curation, and efficient GPU utilisation.
• Enable fast paths from research to production where speed of iteration is critical.
• Lead technical decision-making on training systems, infrastructure, and model development practices.
• Partner with cross-functional leaders to align platform capabilities with product and business goals.
• Mentor and raise the bar for senior engineers and tech leads across the organisation.

Technical scope

• Data platform (embodied AI): Define how data is ingested, curated, enriched, and served for training and evaluation. This includes data quality, sampling, labelling, lifecycle management, and governance.
• Large-scale training systems: Build and evolve training infrastructure capable of handling billions of parameters, large-scale video datasets, and distributed GPU workloads. Focus on efficiency, scalability, and reliability.
• Foundation model training: Own the technical approach to training embodied AI models, including multimodal inputs, training dynamics, monitoring, and productionisation of new methods.

About you

You are a deeply technical leader with hands-on experience building and scaling ML systems in complex environments. You’re comfortable going deep on model training, infrastructure, and data—and you know how to turn research ideas into systems that actually work at scale.

You bring strong judgement, move quickly, and know where to invest for maximum impact. You’re credible with both researchers and engineers and can align teams around clear technical direction.

Essential skills

• Deep expertise in large-scale ML training and model development.
• Strong background in robotics, computer vision, or embodied AI.
• Proven experience building scalable training systems and infrastructure.
• Track record of driving technical strategy across teams.
• Strong understanding of data pipelines, dataset curation, and ML system performance.
• Ability to influence senior stakeholders and operate at exec level.
• Solid grounding in modern ML frameworks (e.g. PyTorch).

Desirable skills

• PhD or equivalent experience in a relevant field.
• Experience with cloud-based ML infrastructure.
• Strong understanding of GPU performance, distributed systems, and hardware/software optimisation.
• Experience contributing to or engaging with the ML research or open-source community.
• Interest in scaling data, compute, and developer productivity in high-growth environments.

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know

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.