AI Systems and Infrastructure Engineer – Alès, France | Visa + Salary Insights

📍 Location: eu

🏷 Type: Contract

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Job Overview

IMT Mines Alès is hiring an AI Systems and Infrastructure Engineer for a 30-month fixed-term contract based in Alès, Occitanie, France. This role sits at the intersection of artificial intelligence infrastructure, research computing, and platform engineering, supporting the MACMIA initiative focused on scaling AI education and AI workforce development. The ideal candidate brings strong experience in Linux systems administration, GPU computing, and AI development environments, with the ability to support researchers, faculty, and students while helping design and operate high-performance computing resources for AI experimentation and teaching.

📅 Job Timeline & Status

This role appears to be in an early-to-mid-cycle hiring phase. With a published deadline of June 28, 2026 and committee review expected on July 20, 2026, applicants still have a strong opportunity window, though competition is likely increasing. Because this is a specialized AI infrastructure and research systems engineering position within a leading French engineering institution, candidates with relevant experience should apply immediately. The role is especially attractive for mid-level infrastructure engineers with expertise in AI platforms and GPU systems.

🌍 Work Eligibility & Location

This opportunity is internationally accessible, particularly for candidates already based in Europe or eligible to work in France. The role is primarily On-site with hybrid flexibility due to infrastructure responsibilities involving physical equipment deployment, GPU systems, and research platform operations. Visa sponsorship may be possible depending on candidate profile, qualifications, and administrative approval.

💰 Salary Intelligence

The compensation is competitive within the French public research and engineering sector. At €34,000–€46,000, the base salary aligns well with university-affiliated AI systems roles, especially considering reduced payroll deductions, vacation benefits, transit reimbursement, and strong work-life balance. For candidates prioritizing research impact, AI infrastructure specialization, and long-term academic-industry career positioning, the compensation package is strong.

📊 Role Breakdown

This is a highly technical AI systems engineering position with a strong operational and research-facing focus. Roughly 40% of the role centers on Linux infrastructure administration, GPU server management, CUDA environments, NVIDIA optimization, virtualization, and maintaining the compute platform powering AI workloads. Around 30% involves supporting AI development environments including Python, TensorFlow, PyTorch, Jupyter-based workflows, and research experimentation infrastructure. Another 20% focuses on user enablement through access management, researcher support, documentation, permissions, and resource allocation. The remaining 10% covers strategic evaluation of emerging AI technologies, hardware recommendations, and project coordination. Key success in this role comes from the ability to operate, optimize, deploy, and scale technical infrastructure while collaborating across research, teaching, and industry partnership teams.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a technically demanding role requiring both infrastructure depth and practical AI systems knowledge. Candidates with 3–5+ years of relevant experience in research computing, platform engineering, DevOps, or AI operations will be the strongest fit. The difficulty is Moderate to High because the role blends systems administration, AI enablement, hardware strategy, and stakeholder support in one position.

🚀 Career Impact

This role offers strong long-term value for engineers building careers in AI infrastructure, MLOps, or research computing. Exposure to academic research, advanced GPU workloads, and institutional-scale AI systems creates strong positioning for future platform engineering leadership, ML infrastructure, and research engineering opportunities.

📋 Key Responsibilities

You will analyze infrastructure requirements with faculty and project stakeholders, develop and maintain the computing platform used by the MACMIA project, and deploy AI-focused hardware and software environments across CERIS. Daily work includes managing Linux systems, maintaining CUDA and GPU performance, supporting Jupyter-based workflows, handling user permissions, monitoring infrastructure usage, and ensuring platform security. You will also collaborate with researchers and engineers to improve experimentation environments while evaluating new AI hardware, storage, and compute technologies aligned with project goals.

🎯 Application Strategy

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🧠 Fit & Positioning Analysis

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📅 Application Signals

Application urgency is high. With the deadline set for June 28, 2026, applicants should apply as early as possible. Competition is expected to be moderate to high due to the strong academic brand and growing demand for AI infrastructure talent across Europe. Interview progression will likely move quickly after the review committee date. “Applications may close without notice.”