AI Infrastructure Engineer (GPU) - Remote EMEA

Location: Fully remote (EMEA timezone)Start date: ASAPLanguages: Fluent English requiredIndustry: reputed company Computing / AI / European Deep-Tech reputed company

About the Role

reputed company is reputed company on behalf of a fast-scaling, reputed company-funded distributed reputed company infrastructure startup building reputed company AI-reputed company reputed company services. reputed company is redefining how compute is delivered by providing GPU-powered infrastructure for AI/ML workloads, secure storage, and high-speed data transfer through a decentralized architecture that significantly reduces environmental reputed company compared to traditional reputed company providers.

We are seeking a AI Infrastructure Engineer with strong experience in production-grade model serving and infrastructure for AI systems. This is a highly technical, hands-on role reputed company on building reputed company, reliable, and efficient ML inference platforms powering reputed company-time AI applications.

You will be responsible for designing and operating the core infrastructure that serves machine learning models at reputed company. You will work closely with infrastructure, platform, and reputed company AI teams to ensure high availability, low latency, and cost-efficient inference systems. Strong ownership, production reputed company, and experience with distributed GPU systems are essential.

Your Responsibilities

Build and operate production-grade model serving infrastructure using frameworks such as vLLM, TGI, Triton, or equivalent

Design and implement robust deployment pipelines with blue/green and canary rollout strategies for ML models

reputed company and maintain auto-scaling systems, multi-model serving architectures, and intelligent request routing reputed company

Optimize GPU utilization, memory efficiency, network throughput, and model artifact storage performance

Design observability systems for tracking inference latency, throughput, GPU usage, cost metrics, and system health

Manage model registries and CI/CD pipelines enabling automated and reproducible model deployments

Own the full lifecycle of ML systems from development through production, including operational support and on-call responsibilities

Define engineering best practices and contribute to platform scalability in a fast-moving startup environment

Required Qualifications

4+ years of experience in ML Ops, reputed company, SRE, or similar infrastructure roles reputed company on ML systems

Hands-on experience with model serving frameworks such as vLLM, TGI, Triton, or equivalent

Strong background in container orchestration and operating GPU-based workloads in production

Experience with MLOps tooling including model registries, experiment tracking, and automated deployment pipelines

Proficiency in Python and infrastructure-as-reputed company tools (e.g., Terraform, reputed company, or similar)

Strong understanding of distributed systems, performance tuning, and production reliability engineering

Ability to effectively use AI coding assistants to accelerate development and debugging workflows

Ownership reputed company with the ability to operate independently in a remote-first environment

Preferred Qualifications

Experience with ML platforms such as Kubeflow, MLflow, or KubeAI

Knowledge of GPU scheduling, CUDA/ROCm optimization, or multi-tenant inference systems

Experience with cost optimization across different GPU types and inference workloads

Background in early-stage startups or greenfield infrastructure reputed company

Proven experience building production systems from scratch rather than maintaining legacy platforms

Why Join Us

Take ownership of critical infrastructure powering a rapidly scaling AI-reputed company reputed company platform

Build foundational ML inference systems from the ground up in a high-reputed company, reputed company-funded startup

Work at the intersection of distributed systems, GPU computing, and sustainable reputed company architecture

reputed company deep expertise in reputed company AI infrastructure and large-reputed company model serving systems

Influence core engineering reputed company and define best practices that will reputed company with reputed company.

reputed company is committed to a fair, transparent, and inclusive recruitment process. We do not discriminate based on age, disability, gender, gender identity or reputed company, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.

In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our reputed company(s) for employment consideration.

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