Model Release Engineer

Overview

In this role you design and build Python services that orchestrate the end-to-end model-release workflow for Wayve’s AI Driver. You integrate feature candidates, trigger training and simulation steps, and productionise cloud-native services on Azure and Kubernetes. You collaborate across teams to provide reliable gates, observability, and tooling that accelerate model deployment. This role combines hands-on programming with platform engineering to scale model release and improve accuracy and safety.

Pay / Benefits

• salary benchmarked against market
• equity participation
• relocation support and visa sponsorship
• hybrid working with in-office and remote time
• learning and development budgets
• comprehensive health and wellbeing benefits

Responsibilities

• Design and implement Python services and microservices for the model-release workflow
• Integrate feature candidates into release branches and automate readiness checks
• Coordinate with training platforms for behavioural-cloning, RL and subsequent steps
• Trigger simulation and on-road tests and surface release status and approvals
• Productionise services on Azure and Kubernetes with emphasis on availability and monitoring
• Use AI coding agents to automate manual work and speed delivery
• Develop end-to-end platform supporting feature integration, training, simulation, testing, approvals, and model promotion
• Develop and maintain platform UI workflows where applicable
• Establish observability and operational tooling with clear visibility into model candidates

Key requirements

• strong software or platform engineering experience building production services in Python
• hands-on Kubernetes experience and cloud-native infrastructure
• production service operations experience; Azure is advantageous
• strong system-design skills across distributed workflows and multi-system integrations
• established observability using metrics, logging, tracing, monitoring and alerting
• ability to collaborate across organisational boundaries and define interfaces
• familiarity with AI coding agents or LLM tools in engineering workflows
• experience with MLOps, model productionisation, training pipelines, evaluation, simulation or model-release workflows is a plus
• front-end development experience with React is beneficial

• collaboration across teams
• ability to negotiate dependable interfaces
• problem-solving mindset
• Python
• Kubernetes
• Azure

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