MLOps Engineer

develop; Brussel; Presencial; EUR 85 000 - 120 000; Tempo integral

Resumo da oferta

Develop is seeking an experienced Senior MLOps Engineer to design, build and operate scalable ML platforms in a large-scale enterprise environment. You will automate model deployment, enhance reliability and optimise performance across production ML systems.

In this hands-on role, you will work with Data Scientists and Platform Engineering teams to implement IaC, CI/CD pipelines, and observability using Docker, Kubernetes and modern MLOps frameworks.

Qualificações

• Proven experience in building and operating MLOps platforms.
• Strong Python programming skills.
• Hands-on with MLflow, Kubeflow or similar.
• Experience with Docker and Kubernetes.
• Experience CI/CD pipelines with GitHub Actions, GitLab CI or Azure DevOps.
• Cloud experience with AWS SageMaker, Azure ML or Vertex AI.
• Infrastructure as Code with Terraform.
• Experience with model serving and monitoring.
• Knowledge of ML lifecycle, feature stores and data pipelines.
• LLMOps and deployment of Generative AI models.

Responsabilidades

• Design and maintain scalable MLOps pipelines and infrastructure.
• Develop automated CI/CD pipelines for ML model training, testing and deployment.
• Deploy and manage ML models in production environments.
• Implement model monitoring, versioning, experiment tracking and performance optimisation.
• Build and maintain containerised ML workloads using Docker and Kubernetes.
• Work closely with Data Scientists, ML Engineers and Platform Engineering teams.
• Implement Infrastructure as Code (IaC) and automated cloud provisioning.
• Improve model lifecycle management, observability and platform reliability.

Conhecimentos

MLOps / ML Platform Engineering

Python programming

CI/CD concepts

Cloud architectures

Ferramentas

Docker

Kubernetes

GitHub Actions

GitLab CI

Azure DevOps

Terraform

MLflow

Kubeflow

SageMaker

Azure ML

Vertex AI

KServe

BentoML

NVIDIA Triton

Prometheus

Grafana

Descrição da oferta de emprego

Develop are looking for an experienced Senior MLOps Engineer to support the development, deployment and optimisation of production-grade Machine Learning infrastructure within a large-scale enterprise environment.

This is a hands-on engineering role focused on building scalable ML platforms, automating model deployment and improving the reliability and performance of machine learning systems.

Key Responsibilities:

• Design, build and maintain scalable MLOps pipelines and infrastructure.
• Develop automated CI/CD pipelines for machine learning model training, testing and deployment.
• Deploy and manage ML models in production environments.
• Implement model monitoring, versioning, experiment tracking and performance optimisation.
• Build and maintain containerised ML workloads using Docker and Kubernetes.
• Work closely with Data Scientists, ML Engineers and Platform Engineering teams.
• Implement Infrastructure as Code (IaC) and automated cloud provisioning.
• Improve model lifecycle management, observability and platform reliability.

Essential Technical Skills:

• Strong commercial experience in MLOps or ML Platform Engineering.
• Advanced Python programming skills.
• Hands‑on experience with MLflow, Kubeflow or similar MLOps frameworks.
• Strong knowledge of Docker and Kubernetes.
• Experience building CI/CD pipelines using GitHub Actions, GitLab CI or Azure DevOps.
• Cloud experience with AWS SageMaker, Azure Machine Learning or Google Vertex AI.
• Infrastructure as Code using Terraform.
• Experience with model serving, monitoring and automated retraining pipelines.
• Understanding of ML model lifecycle management, feature stores and data pipelines.
• LLMOps and deployment of Generative AI models.
• Model serving frameworks such as KServe, BentoML or NVIDIA Triton.
• Distributed model training and inference.
• Monitoring tools such as Prometheus and Grafana.