AI/ML Platform Engineer

Company

is an ecosystem of 60+ successful brands working together across 22 European countries to provide its 3.5 million SMB customers with everything they need to succeed online by offering best-in-class expertise and services.

's brands are a mix of traditional hosting businesses that offer services from domain names, email, shared hosting, e-commerce, and server hosting solutions and, as specialist SaaS providers, adjacent products such as compliance, marketing tools, and team collaboration products. This broad product offering makes it a one-stop partner for online businesses and entrepreneurs across Europe.

AI/ML Platform Engineer

We are looking for an AI/ML Platform Engineer to design, build, and maintain our machine learning and AI infrastructure platform. This role is critical to enabling our data science and AI teams to deploy, scale, and manage ML models efficiently across multi-GPU environments. You'll be responsible for creating robust, scalable platforms that support the full ML lifecycle from model training to inference, with a particular focus on LLM deployment and management.

Key Responsibilities

Platform Development & Management

Design and implement scalable ML/AI platforms supporting model deployment across multi-GPU nodes

Build and maintain infrastructure for LLM inference serving, including optimization for latency and throughput

Develop automated deployment pipelines for machine learning models using containerization and orchestration technologies

Create self-service tools and APIs that enable data scientists to deploy models independently

Infrastructure & Operations

Manage and optimize GPU cluster resources, ensuring efficient utilization and cost management

Implement monitoring, logging, and alerting systems for ML workloads and model performance

Design disaster recovery and backup strategies for critical ML infrastructure

Maintain high availability and reliability standards for production ML services

DevOps & Automation

Build CI/CD pipelines specifically tailored for ML model deployment and updates

Automate infrastructure provisioning using Infrastructure as Code (IaC) principles

Implement model versioning, rollback capabilities, and A/B testing frameworks

Develop automated scaling solutions for varying inference workloads

Collaboration & Support

Work closely with data science teams to understand requirements and optimize deployment workflows

Provide technical guidance on best practices for model deployment and infrastructure usage

Collaborate with security teams to implement secure ML model serving practices

Document platform capabilities, procedures, and troubleshooting guides

Required Qualifications

Professional Experience

3+ years of experience in Platform engineering, DevOps, or infrastructure roles

2+ years of experience specifically with ML/AI infrastructure or platforms

Technical Skills

Cloud Platforms: 3+ years experience with AWS, Azure, or GCP, particularly GPU-enabled services

Containerization: Proficiency with Docker and Kubernetes, including GPU scheduling and resource management

Infrastructure as Code: Experience with Terraform, CloudFormation, or similar tools

Programming: Strong skills in Python and at least one additional language (Go, Java, or Rust)

ML Frameworks: Familiarity with PyTorch, TensorFlow, and model serving frameworks (TorchServe, TensorFlow Serving, etc.)

Platform & Operations Experience

Experience building and maintaining production ML platforms or similar infrastructure (KubeFlow, MLFlow, SageMaker, etc)

Knowledge of GPU computing, CUDA, and multi-GPU distributed computing

Understanding of ML model lifecycle management and MLOps practices

Experience with monitoring tools (Prometheus, Grafana, ELK stack)

Experience with streaming data processing (Kafka, Kinesis, Pulsar)

Familiarity with service mesh technologies and API gateways

AI/ML Knowledge

Understanding of large language models (LLMs) and inference optimization techniques

Knowledge of model quantization, pruning, and other optimization methods

Experience with distributed training and inference across multiple GPUs/nodes

Familiarity with vector databases and embedding storage solutions

Right to Work

At any stage, please be prepared to provide proof of eligibility to work in the country you're applying for. Unfortunately, we are unable to support relocation packages or sponsorship visas.

ESG

"At , our commitment to caring for the environment and each other is at the heart of everything we do. Our latest impact report showcases our ongoing ESG efforts and ambitious sustainability goals. Interested in learning more about our dedication to making a positive impact? ."

"Come as you are"

Everyone is welcome here. Diversity & Inclusion are at our core. Far above any technical competence, we value respect, openness, and trusted collaboration. We do not tolerate intolerance.

Department

AI

Locations

Budapest- Hungary

Remote status

Fully Remote

Seniority

Mid - Senior level

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