AI Infrastructure Engineer (GPU) - Remote EMEA

📋 Description

• • AI Infrastructure Engineer (GPU) role focused on building and operating production-grade model serving infrastructure for AI/ML workloads in a fast-scaling, well-funded distributed cloud infrastructure startup.
• • Day-to-day responsibilities include designing and operating scalable ML inference platforms using frameworks like vLLM, TGI, Triton; implementing deployment pipelines with blue/green and canary strategies; developing auto-scaling systems and intelligent request routing; optimizing GPU utilization, memory efficiency, and network throughput; designing observability systems for latency, throughput, and cost metrics; managing model registries and CI/CD pipelines; owning the full lifecycle of ML systems from development to production, including on-call support; and defining engineering best practices for platform scalability.
• • The company is redefining compute delivery by providing GPU-powered infrastructure for AI/ML workloads, secure storage, and high-speed data transfer through a decentralized architecture that reduces environmental impact compared to traditional cloud providers.
• • The role offers the opportunity to take ownership of critical infrastructure powering a rapidly scaling AI-native cloud platform, build foundational ML inference systems from the ground up, work at the intersection of distributed systems, GPU computing, and sustainable cloud architecture, gain deep expertise in next-generation AI infrastructure, and influence core engineering decisions that will scale with the company.