MLOPS Engineer

Meerab Group; Brussel Hoofdstad; On-site; EUR 65,000 - 90,000; Full time

Job summary

Meerab Group in Belgium is seeking an experienced ML Ops/Infrastructure Engineer to design, build, and operate production-grade ML systems centered on LLMs across hybrid on-prem and cloud infrastructure.

You will deploy, test, monitor, and manage models in containerized environments, develop the LLMOps lifecycle (data prep, fine-tuning, evaluation, deployment, monitoring), and create CI/CD pipelines and data tooling. Strong Python, Kubernetes, and cloud experience are required.

Qualifications

• Experience managing on-premise and/or cloud LLM/MLOps infra.
• Proficiency with containerisation and orchestration platforms like Kubernetes, Docker, Podman, EKS, PKS.
• Hands-on with MLflow, TensorFlow (TFX), Airflow and major cloud providers (AWS or EU cloud).
• Strong Python, Unix/Bash, and IaC tools (Terraform or CloudFormation).
• Familiarity with Kafka, Redis, RabbitMQ and NoSQL DBs (OpenSearch, MongoDB).

Responsibilities

• Design, build, and maintain production-grade ML systems centering on LLMs across hybrid on-prem/cloud infrastructure.
• Deploy, test, monitor, and manage ML models in containerised environments.
• Develop and evolve the LLMOps lifecycle, including data preparation, fine-tuning, evaluation, deployment, and monitoring.
• Create CI/CD pipelines, orchestration solutions, and data versioning tools for ML workflows.
• Implement automated anomaly detection, performance tracking, and cost-optimisation for ML pipelines.

Tools

Kubernetes

Docker

Podman

EKS

PKS

Terraform

CloudFormation

Kafka

Redis

RabbitMQ

OpenSearch

MongoDB

MLflow

TensorFlow

Airflow

Job description

Key responsibilities

• Design, build, and maintain production‑grade ML systems centered on LLMs across hybrid on‑prem/cloud infrastructure.

• Deploy, test, monitor, and manage ML models in containerised environments.

• Develop and evolve the LLMOps lifecycle, including data preparation, fine‑tuning, evaluation, deployment, and monitoring.

• Create CI/CD pipelines, orchestration solutions, and data versioning tools for ML workflows.

• Implement automated anomaly detection, performance tracking, and cost‑optimisation for ML pipelines.

Required qualifications

• Strong expertise in managing on‑premise and/or cloud LLM/MLOps infrastructure.

• Proficiency with containerisation and orchestration platforms such as Kubernetes, Docker, Podman, EKS, PKS.

• Hands‑on experience with MLflow, TensorFlow (TFX), Airflow, and major cloud providers (AWS or EU cloud).

• Solid programming skills in Python, Unix/Bash, and infrastructure‑as‑code tools like Terraform or CloudFormation.

• Familiarity with messaging systems (Kafka, Redis, RabbitMQ) and NoSQL databases (OpenSearch, MongoDB).

Nice to have

• Knowledge of encryption mechanisms and ML security best practices.

• Experience with the European Commission grant management ecosystem (eGrants).