14 минут назад
Model Release Engineer (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Model Release Engineer (AI): Building and operating the platform that moves AI Driver models through feature integration, training, simulation, on-road testing, evaluation, approval, and production release with an accent on distributed systems, reliability, and observability. Focus on automating cross-team workflows, integrating model engineering and MLOps systems, and creating transparent release processes for scalable, business-critical platforms.
Location: London, United Kingdom; full-time hybrid role based in the London office
Company
develops AI Driver technology and platforms for autonomous driving.
What you will do
- 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 Model Engineering, MLOps, Simulation, Measurement, On-Road Testing, Operations, and Release Management systems.
- Collaborate across teams to define requirements, agree technical interfaces, and resolve workflow and delivery conflicts.
- Improve platform reliability, scalability, performance, 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 repetitive engineering tasks.
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, define technical interfaces, and resolve conflicting priorities.
- Experience operating cloud-based services with Kubernetes, including understanding of reliability, scalability, and performance.
- Practical knowledge of observability, monitoring, alerting, and service-health metrics.
- Confidence using AI coding tools and agents, with a pragmatic, ownership-driven approach to evolving requirements.
Nice to have
- 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 with React.
- Experience supporting highly available platforms in business-critical production workflows.
Culture & Benefits
- Hybrid working combines time in offices and workshops with time working from home.
- Office-based collaboration supports innovation, relationships, culture, and learning.
Будьте осторожны: если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого - это мошенники. Обязательно жмите "Пожаловаться" или пишите в поддержку. Подробнее в гайде →