The role
We’re looking for a Model Release Engineer to build the platform that moves Wayve’s AI models from promising new features through training, simulation, on-road testing and release. You’ll automate a complex process spanning multiple systems and teams, creating a scalable, reliable and transparent path to production. Working across the full model-release lifecycle, you’ll directly improve how quickly and confidently we deploy new AI Driver models.
Key Responsibilities
- Design and build services and workflows that automate the end-to-end model-release process, from feature integration through training, evaluation, approval and promotion.
- Integrate the platform with systems owned by Model Engineering, MLOps, Simulation, Measurement, On-Road Testing, Operations and Release Management.
- Work closely with teams across Wayve to understand their requirements, agree interfaces and resolve technical or delivery conflicts across shared workflows.
- Improve the reliability, scalability and observability of the platform through effective monitoring, alerting and operational tooling.
- Provide clear visibility of model candidates, their progress, evaluation results, approvals and release status.
- Use AI-assisted development and agentic workflows to automate manual engineering tasks and accelerate delivery.
About you
In order to set you up for success as a Model Release Engineer at Wayve, we’re looking for the following skills and experience.
Essential
- Strong software engineering experience, including building production services and platforms in Python.
- Experience designing distributed systems, APIs or microservices that connect multiple tools and workflows.
- Proven ability to collaborate across organisational boundaries, align stakeholders, agree technical interfaces and work through conflicting priorities.
- Experience operating cloud-based services using Kubernetes, with a good understanding of reliability, scalability and performance.
- Practical knowledge of observability, monitoring and alerting, including defining meaningful service-health metrics.
- Confidence using AI coding tools and agents to improve engineering productivity and automate repeatable work.
- A pragmatic, ownership-driven approach and the ability to make progress where requirements and processes are still evolving.
Desirable
- Experience with MLOps, machine-learning infrastructure or production model-training and release pipelines.
- Understanding of model evaluation, simulation, experiment orchestration or approval-gated release processes.
- Front-end development experience, ideally using React.
- Experience supporting highly available platforms used within business-critical production workflows.
This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home.
