AI Platform Support Engineer (EMEA)

Responsibilities

We are representing a confidential AI infrastructure organization seeking an AI Platform Support Engineer to join their EMEA Customer Experience team in London. In this role, you will serve as a technical partner to ML engineering teams running large-scale training and inference workloads in production.

Your core responsibilities include:

• Partnering directly with customer engineering teams to diagnose and resolve complex distributed systems and ML infrastructure issues
• Acting as a technical advisor during high-impact incidents and platform degradation events
• Investigating failures involving distributed training, Kubernetes orchestration, GPU allocation, networking, and storage systems
• Troubleshooting framework-related issues including distributed PyTorch, CUDA, NCCL, and inference serving
• Analyzing logs, metrics, traces, and system behavior to isolate root causes in containerized workloads
• Supporting customers scaling workloads across multi-node GPU systems and diagnosing performance bottlenecks
• Identifying recurring patterns across customer issues and driving long-term reliability improvements
• Contributing to post-incident reviews, building internal tooling, automation, documentation, and runbooks
• Partnering with infrastructure, networking, and platform engineering teams to improve observability and troubleshooting workflows

Schedule: This role requires working one of two EMEA shifts (9AM–7PM CET/CEST): Saturday–Tuesday or Thursday–Sunday. The position is hybrid with at least 2 days per week in the London office.

What We're Looking For

Required Infrastructure & Systems Experience:

• Strong software engineering and systems troubleshooting background
• Experience with Kubernetes and containerized environments
• Linux systems knowledge, including networking, storage, process management, and performance tuning
• Experience with cloud infrastructure and distributed systems
• Familiarity with observability and debugging tools such as Prometheus, Grafana, or OpenTelemetry

Required ML Infrastructure Experience:

• Hands-on experience operating machine learning workloads in production or research environments
• Experience with distributed ML systems and tooling such as PyTorch, CUDA, or NCCL
• Familiarity with GPU infrastructure and orchestration
• Experience troubleshooting performance, reliability, or scaling issues in ML infrastructure
• Understanding of the operational challenges involved in running ML systems at scale

Required Collaboration Skills:

• Strong communication skills and ability to work directly with highly technical customers and engineering teams
• Comfortable operating in fast-moving, highly ambiguous environments
• Enjoys solving complex technical problems collaboratively

Nice-to-Have Qualifications:

• Experience with large-scale model training or distributed inference systems
• Familiarity with Ray, Kubeflow, Slurm, or similar distributed scheduling platforms
• Experience with InfiniBand, RDMA, or high-performance networking
• Experience operating bare-metal infrastructure
• Familiarity with storage systems commonly used in ML environments
• Experience working at an AI infrastructure, cloud, MLOps, or developer tooling company
• Experience writing automation, tooling, or scripts in Python or similar languages

Important: This is not a traditional help desk, ticket routing, or customer success role. This position is for engineers who enjoy solving difficult technical problems while working closely with other engineers. Visa sponsorship is not available at this time.

How We Work with You

Our talent team at Get A Job.ai partners with leading organizations in the AI infrastructure space to connect exceptional technical professionals with career-defining opportunities. When you apply through our platform, a dedicated recruiter will review your background and conduct an initial screening to understand your experience and goals.

If your profile aligns with our client's requirements, we will submit your application and coordinate the interview process. We ask that candidates apply exclusively through Get A Job.ai and not contact the client organization directly, as this allows us to best represent your interests throughout the hiring process.

Pay

Pay via Get A Job.ai: £75,000–£95,000 GBP annually. Compensation reflects experience, skills, and role expectations. Eligible roles may include discretionary bonus, equity component, and comprehensive benefits.

Get A Job.ai is an equal opportunity recruiter. We are committed to fostering inclusive hiring practices and provide equal opportunities to all applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.