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MLOps & AI Infrastructure Engineer (f/m/d)

NXAI
Linz, OÖ

Jetzt bewerben

Details zur Stelle

Vollzeit
vor 2 Stunden

Qualifikationen

Master

Vollständige Stellenbeschreibung

Based in Linz, Austria, NXAI is a leading center for European AI innovation, turning advanced research into real-world industrial applications. Focused on next-generation xLSTM architectures, we offer companies a sovereign, on-premise alternative to US hyperscalers. A prime example is our zero-shot time series foundation model, TiRex, which delivers industrial enterprises a true technological edge - operating up to 50× more efficiently than traditional transformer models.

At NXAI, we're always excited to meet forward-thinking minds eager to shape the future of AI. As we expand our capabilities and deploy models at massive scale, we are looking for an MLOps Engineer (f/m/d) to design, scale and orchestrate the high-performance GPU clusters powering the next generation of AI.

In this role, you will shape the future of NXAI's AI infrastructure by:

Scaling AI Architecture: Designing, operating and automating our high-performance infrastructure across cloud, HPC and on-premise environments.
Empowering Research: Collaborating with Research and Applied Research teams to translate cutting-edge AI models into scalable, production-ready systems.
Optimizing GPU Clusters: Managing and fine-tuning large-scale GPU compute, storage and networking resources for intensive workloads.
Driving MLOps & Orchestration: Building robust machine learning pipelines and managing orchestration platforms using Kubernetes and Slurm.
Ensuring Excellence: Implementing modern CI/CD workflows and maintaining the highest standards for system reliability, security, and observability.

What We Ask

A hands-on problem solver passionate about building resilient systems that accelerate AI deployment.
Deep experience with Linux-based production environments, distributed systems, and containerization (Docker/Podman).
Proven track record with workload schedulers (Slurm), Kubernetes, CI/CD pipelines (e.g., GitHub Actions) and Python scripting.
Hands-on expertise with GPU computing environments, storage optimization and building/monitoring MLOps pipelines.
Bonus Points: Experience with modern AI frameworks (like PyTorch) and supporting large-scale model training environments.

What You’ll Get:

The Mission & Impact:

Shape the Future of AI: The chance to contribute to technology that has the potential to redefine how AI systems are built, trained and deployed.
Challenging the Status Quo: Work directly with leading AI researchers, including the creators of xLSTM, on technologies that challenge the current transformer paradigm.
A Key Position: A central role in enabling foundation model research, industrial AI applications and efficient AI systems that can run from cloud-scale infrastructure down to edge devices.
Ownership & Autonomy: Significant ownership, autonomy and the ability to shape our infrastructure, tooling and engineering culture within a highly talented, research-driven team.

Our Core Benefits:

Flexibility: Remote and hybrid work options tailored to your lifestyle.
Mobility Support: We fully cover either your Klimaticket (public transport) or your parking spot.
Relocation Support: Moving to Austria? We will support you through the entire relocation and visa process to make your transition as smooth as possible.
Growth & Culture: Access to international tech conferences, regular team events and our weekly onsite team lunch to stay connected.

Compensation:

Competitive Salary: A market-aligned salary package tailored to your experience. The starting salary for this position is €4,611 gross per month (paid 14 times per year). Depending on your specific profile, technical skills and development potential, a significant overpayment is of course possible.
Financial Upside (VSOP): Participation in our Virtual Stock Option Plan (VSOP) – because we want you to truly own a piece of the future you are building.

Jetzt bewerben

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In this role, you will shape the future of NXAI's AI infrastructure by:

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