Requirements
Requires strong software engineering experience in Python and expertise in designing distributed systems or microservices. Candidates should have experience with cloud-based services, Kubernetes, and a collaborative approach to working across organizational boundaries.
Job Description
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.