AI/ML Application Expert (HPC & Supercomputing) – Linköping, Sweden | Visa + Salary Insights

📍 Location: eu

🏷 Type: Not specified

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Job Overview

This role targets a Senior-Level AI/ML specialist working at the intersection of high-performance computing (HPC), distributed systems, and deep learning. Based at :contentReference[oaicite:0]{index=0} within the National Supercomputer Centre, the position focuses on enabling large-scale research through AI infrastructure, GPU computing, and advanced data workflows. Ideal candidates bring 5+ years experience in AI engineering or scientific computing, with strong capabilities in PyTorch, TensorFlow, and Linux environments, combined with the ability to collaborate across research domains.

🌍 Work Eligibility & Location

This opportunity is globally accessible due to visa sponsorship and structured relocation support. While the role is primarily onsite/hybrid in Sweden, the flexibility of 40% remote work enables partial international adaptability. English ensures accessibility, but regional collaboration favors candidates comfortable working within European research ecosystems.

💰 Salary Intelligence

Although not explicitly stated, compensation aligns with Nordic public-sector benchmarks for senior AI and HPC specialists. The estimated €60K–€85K range is competitive when adjusted for Sweden’s benefits system, including work-life balance, parental support, and research funding access. The real value lies in infrastructure exposure and research collaboration rather than pure salary maximization.

📊 Role Breakdown

This position is structured around three interconnected domains: AI computation (40%), data processing and infrastructure (35%), and training and enablement (25%). You will optimize distributed deep learning workflows using multi-GPU systems, ensuring efficient scaling of generative AI models and scientific simulations. A key responsibility includes designing data pipelines that efficiently move large datasets across distributed storage systems and compute clusters.

You will also develop services such as containerized environments and secure workflows for sensitive datasets. Collaboration is central: you will interface with researchers across domains like genomics and physics to translate computational needs into scalable solutions. Additionally, you will lead training sessions and workshops, enabling researchers to leverage AI/ML tools and HPC resources effectively. This hybrid role blends engineering execution, advisory responsibilities, and educational impact at scale.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This role sits at the intersection of AI engineering and scientific computing, making it highly selective. The 5+ years requirement combined with niche expertise in distributed training and HPC systems significantly narrows the candidate pool. However, global visibility and research prestige increase competition intensity, particularly among candidates from academia and advanced AI labs.

🚀 Career Impact

This role delivers high long-term career leverage by positioning you within national AI infrastructure initiatives. You gain deep expertise in scalable AI systems, a critical skill for future roles in AI platform engineering, research leadership, or large-scale ML systems design. The exposure to interdisciplinary research expands your ability to work across industries.

📋 Key Responsibilities

You will develop and optimize AI/ML workflows on large-scale GPU clusters, ensuring efficient parallel training of models. A core task is to improve performance of distributed systems by refining data pipelines and storage integration. You will also design and deploy services such as containerized environments and secure data solutions.

Additionally, you will collaborate with researchers to identify computational needs and translate them into scalable architectures. The role includes delivering training programs on AI tools, HPC usage, and distributed workflows. You will also monitor emerging technologies and contribute to infrastructure procurement decisions, ensuring the center remains at the forefront of AI and supercomputing innovation.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is personalized by seniority.

🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role shows moderate urgency with a defined deadline, but hiring is selective due to specialization. Expect high competition from candidates with research or HPC backgrounds. Early application increases visibility, especially if aligned with distributed AI systems expertise.

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✅ Job Source & Verification

This listing is sourced directly from the official recruitment portal of Linköping University, ensuring high credibility and authenticity. All details reflect the most recent posting, with last updated timeline aligned to the application deadline of May 2026. Candidates should verify updates on the official site before applying.