Junior MLOps Engineer

A2G Consulting BV (A2G Technologies) • Netherlands

Visa Sponsorship

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AI Summary

We are looking for a motivated Junior MLOps Engineer to help build and maintain scalable infrastructure for AI and machine learning workloads in a research and engineering environment. This role focuses on cloud platforms, GPU-based computing, and automation for ML systems. The ideal candidate will have experience with cloud platforms, container orchestration, and programming skills in Python and Bash.

Key Highlights

Support the development and operation of AI/ML infrastructure in cloud and high-performance computing environments.

Deploy and manage containerized workloads using Kubernetes.

Implement and maintain machine learning pipelines and model deployment workflows.

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Key Responsibilities

Support the development and operation of AI/ML infrastructure in cloud and high-performance computing environments.

Deploy and manage containerized workloads using Kubernetes.

Implement and maintain machine learning pipelines and model deployment workflows.

Work with AI platforms such as Kubeflow, MLflow, and NVIDIA Triton Inference Server.

Automate infrastructure and deployment processes using Infrastructure-as-Code tools.

Collaborate with research, engineering, and data science teams to support AI/ML projects.

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Technical Skills Required

Kubernetes Python Bash Microsoft Azure Google Cloud Amazon Web Services GPU-accelerated environments Terraform Ansible

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Benefits & Perks

Competitive Gross Salary

20 days of holiday per year

Encourage Personal Development - Certification

Income Tax Return Filing

Visa Sponsorship for Candidate & Dependants

Possibility of bonus

Job Description

Contract: 12 months (subject to extension).

Location: Eindhoven, Netherlands.

Salary: Not a constraint for the right candidate!

Experience: 8-10 years.

Hybrid: 2 days Work from Home 3 days Work from Office

Your Profile & DNA:

We are looking for a motivated Junior MLOps Engineer to help build and maintain scalable infrastructure for AI and machine learning workloads in a research and engineering environment. This role focuses on cloud platforms, GPU-based computing, and automation for ML systems.

Roles & Responsibilities

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