5 hours ago
London, United KingdomSenior
Responsibilities
- Design and build services and workflows that automate model release 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.
- Collaborate across teams to understand requirements, agree technical interfaces, and resolve conflicts across shared workflows.
- Improve platform reliability, scalability, and observability through monitoring, alerting, and operational tooling.
- Provide visibility into model candidates, progress, evaluation results, approvals, and release status.
- Use AI-assisted development and agentic workflows to automate manual engineering tasks and accelerate delivery.
Requirements
- Strong software engineering experience building production services and platforms in Python.
- Experience designing distributed systems, APIs, or microservices that connect multiple tools and workflows.
- Ability to collaborate across organizational boundaries, align stakeholders, agree technical interfaces, and resolve conflicting priorities.
- Experience operating cloud-based services using Kubernetes with an understanding of reliability, scalability, and performance.
- Practical knowledge of observability, monitoring, alerting, and service-health metrics.
- Confidence using AI coding tools and agents to improve productivity and automate repeatable work.
- A pragmatic, ownership-driven approach with the ability to work through evolving requirements and processes.
- Experience with MLOps, machine-learning infrastructure, or production model-training and release pipelines is desirable.
- Understanding of model evaluation, simulation, experiment orchestration, or approval-gated release processes is desirable.
- Front-end development experience, ideally using React, is desirable.
- Experience supporting highly available platforms used in business-critical production workflows is desirable.
Benefits
- Full-time role based in London.
- Hybrid working policy combining time in Wayve offices and workshops with time working from home.
- Inclusive interview accommodations and adjustments are available upon request.
