Staff Software Engineer, Model Development Platform (Cloud Infrastructure & AI Systems)

wayve • United State

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AI Summary

Lead the architecture and development of Wayve’s cloud-based AI model lifecycle platform, ensuring scalable, secure, and reliable infrastructure for autonomous driving models. Own authentication, microservices, deployment pipelines, and cross-team technical leadership to accelerate research and safe on-road testing. Requires 7+ years in large-scale distributed systems, cloud platforms, and hands-on engineering with security and reliability expertise.

Key Highlights

Architect and evolve scalable, secure cloud services for Wayve’s AI model lifecycle (data, training, evaluation, testing)

Own identity/access control, microservices, and deployment infrastructure with end-to-end ownership

Drive reliability (SLAs/SLOs), observability, and CI/CD while mentoring engineers and shaping technical direction

Key Responsibilities

Design and maintain scalable, reliable cloud services for Wayve’s AI model lifecycle (data pipelines, training workflows, experiment scheduling, evaluation, and on-road testing)

Lead identity/access control (IAM) and security architecture to ensure sensitive model/data protection across platform services

Define microservices/micro-frontend patterns, boundaries, and shared tooling for independent team development while ensuring system interoperability

Build CI/CD, progressive delivery, and rollback infrastructure with observability, alerting, and self-healing capabilities

Set SLAs/SLOs for availability, latency, and performance, and drive practices to meet them

Collaborate cross-functionally with Product, Research, Design, and Operations to align technical solutions with user needs and platform roadmap

Mentor engineers through design reviews, code reviews, and hands-on problem-solving in backend services, web apps, and cloud infrastructure

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Technical Skills Required

Cloud Platform Architecture (e.g., AWS/GCP/Azure) Distributed Systems & Microservices Authentication & Authorization (OAuth2/OIDC, RBAC)

Benefits & Perks

Market-benchmarked annual salaries

Meaningful equity and long-term ownership

Relocation support and visa sponsorship where applicable

Hybrid working with core hours and access to vehicle labs

Comprehensive benefits (health insurance, dental, parental leave, retirement, wellbeing support)

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Nice to Have

Experience with ML operations (training, evaluation, experiment tracking, artifact management)

Familiarity with distributed compute (Spark, Ray, Airflow, MLflow) or data pipelines

Knowledge of service mesh, API gateways, or progressive-delivery tooling

Background in autonomous systems, robotics, or safety-critical domains

Job Description

Before the detail, here's the challenge you'd help us solve.We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.Here’s what this particular role covers.🛠️ About the role

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