Staff SRE, AI Infrastructure

3 дн. назад

United KingdomEuropeLeadOnsite

gpucloudsite reliability engineeringinfrastructure

Founding Staff SRE role focused on building and scaling reliability foundations of large-scale AI systems and GPU compute infrastructure.

О компании

Founded in 2017, is the leading developer of Embodied AI technology.  Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.
Our vision is to create autonomy that propels the world forward.  Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.  In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.
At , your contributions matter.  We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.  
Make the experience that defines your career!

Обязанности

This is a rare opportunity to be a founding Staff SRE shaping the reliability of large-scale AI systems and GPU compute infrastructure from the ground up.
As a Staff Cloud Site Reliability Engineer at , you will build and scale the reliability foundations of our AI cloud platform. This includes our Model Development Platform (powering end-to-end model development from raw data to on-road experimentation) and our GPU Compute platform (large-scale, multi-tenant GPU fleets and scheduling systems driving model training and inference at scale).
This is a founding Cloud SRE role. You won’t inherit a mature SRE function, you’ll help create it. You will define the frameworks, automation, and operational standards that ensure our model development infrastructure, distributed systems, and large compute clusters operate predictably, efficiently, and at scale.
This role sits at the intersection of AI research, large-scale cloud infrastructure, and production operations. Your work will directly enable faster model training, reliable experimentation, and scalable AI deployment by ensuring our cloud infrastructure is resilient and performant.

Требования

In order to set you up for success as a Cloud Site Reliability Engineer at , we’re looking for the following skills and experience.

Другое

Own the reliability, availability, and performance of the Model Dev Platform and GPU Compute environments.
Define and operationalise SLOs, SLIs, and error budgets across platform services.
Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.
Partner with ML, platform, and software teams to establish clear production readiness standards.
Participate in a 24/7 on-call rotation as first-line response for cloud and cluster-related incidents.
Lead incident triage, escalation, communications, and root cause analysis.
Translate post-incident learning into durable architectural or automation improvements.
Continuously reduce alert noise and recurring operational burden.
Design and operate monitoring, logging, tracing, and alerting systems that enable rapid detection and recovery.
Build dashboards that reflect real user-centric platform health (not just infrastructure metrics). Improve deployment safety through better change management, validation, and rollback mechanisms.
Build automation for cluster operations, training workflows, remediation, and scaling tasks.
Implement self-healing patterns and resilient recovery workflows.
Harden CI/CD and release processes to improve deployment safety and velocity.
Support infrastructure-as-code and policy-driven guardrails to ensure secure, reliable cloud environments.
Proven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.
Experience operating GPU-backed environments or large-scale ML infrastructure.
Experience running model training or inference pipelines in production (MLOps).
Strong Kubernetes experience, including operating production clusters.
Hands-on experience running production workloads in AWS, GCP, or Azure.
Experience operating complex distributed systems in production, ideally including compute-heavy or high-performance workloads.
Experience working with large compute clusters; exposure to AI/ML training or inference workloads strongly preferred.
Strong Linux fundamentals and proficiency in at least one scripting or systems language (e.g. Python, Go, C++) with a bias toward automation.
Deep troubleshooting skills across networking, storage, distributed systems, and performance at scale.
Experience designing and operating observability stacks (e.g. Datadog, Prometheus, Grafana, OpenTelemetry).
Clear communication skills, including leading incidents, writing postmortems, and influencing teams to prioritise reliability improvements.
Familiarity with infrastructure-as-code (e.g. Terraform) and secure cloud production environments.
Experience defining and running SLOs/SLIs and building reliability programs across multiple teams.
Experience as an early or founding SRE hire establishing processes from scratch.
Interest in helping shape and grow a Cloud SRE function, with potential to take on leadership responsibilities over time.
This is a full-time role based in our office in London (2 days a week in the office).  At 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.
is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.
We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. At we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition  (including breastfeeding) or any other basis as protected by applicable law.  
For more information visit Careers at . 
To learn more about what drives us, visit Values at  
For US candidates only, please visit E-Verify Notice and Participation and Right to Work
DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.