At a Glance
- Tasks: Support and optimise AI compute infrastructure for cutting-edge projects.
- Company: Join the Italian Institute of Artificial Intelligence, a leader in AI innovation.
- Benefits: Competitive salary, advanced tech resources, and a collaborative work environment.
- Other info: Flexible hybrid work arrangements and opportunities for career growth.
- Why this job: Make a real impact on AI workloads and work with top-tier technologies.
- Qualifications: Experience with HPC clusters, GPU architectures, and AI workload optimisation.
The predicted salary is between 50000 - 70000 £ per year.
The Italian Institute of Artificial Intelligence (AI4I) is seeking a hands-on HPC / AI Specialist to support and optimize the compute infrastructure powering the AI Foundry and Deployment activities. At AI4I, you will work on a state-of-the-art AI computing environment built with best-in-class technologies acquired over the past year, including next-generation GPU systems such as NVIDIA B200 accelerators and high-performance distributed storage solutions such as VAST. This infrastructure is designed to support AI training, fine-tuning, and inference workloads for both research and industrial deployment.
In this role, you will focus on optimizing performance and providing direct technical support to internal users and clients running AI workloads, while contributing to the continuous evolution and improvement of the system design. You will act as a key interface between the machine infrastructure and the teams executing AI workflows, ensuring efficient, stable, and predictable operations.
Hybrid work: Flexible arrangements may be negotiated. The position will remain open until it is filled and multiple candidates may be hired.
About the Role
As HPC / AI Specialist at AI4I, you will operate at the intersection of infrastructure operations and applied AI execution. You will ensure that engineers, researchers, and deployment teams can efficiently run training, fine-tuning, inference, and data-intensive pipelines on shared compute resources. This is a cross-unit role shared 50% with the new Deployment Unit, working closely with both infrastructure and client-facing teams.
You will work closely with:
- AI engineers and ML / GenAI teams running training, fine-tuning, and inference workloads
- Cloud / DevOps engineers operating the private cloud
- The Deployment Unit supporting industrial AI clients
- Hardware vendors and infrastructure partners
This role is strongly operational and performance-oriented, with a focus on workload efficiency, system tuning, AI workload optimization, and user support.
Key Responsibilities
- Operate and maintain Linux-based HPC clusters supporting AI training, fine-tuning, and inference workloads
- Manage GPU and CPU compute environments, including workload scheduling, resource isolation, and performance tuning
- Support distributed and software-defined storage systems used for large-scale datasets
- Act as the primary technical interface between infrastructure operations and internal or external users running AI workflows
- Provide hands-on technical support for AI workload optimization, including distributed training and parameter-efficient fine-tuning of foundation models on HPC infrastructure
- Support foundation model fine-tuning workflows, including configuration of data pipelines, checkpoints, runtime settings, and GPU memory optimization in HPC environments
- Optimize resource utilization and workload performance across multi-tenant environments
- Support containerized workloads running on shared compute infrastructure
- Monitor system health, performance, and capacity; troubleshoot user-facing production issues
- Contribute to the continuous improvement and evolution of system architecture in collaboration with infrastructure teams
- Support internal users and clients with debugging, environment setup, and best practices for scalable AI execution
Required Qualifications
- Solid background in CPU and GPU architectures and performance characteristics
- Experience operating HPC clusters or large-scale compute environments
- Hands-on experience with distributed and software-defined storage systems (e.g., VAST or equivalent)
- Experience with workload managers and job schedulers (e.g., Slurm or equivalent)
- Experience troubleshooting performance bottlenecks in compute or storage environments
- Practical understanding of AI training and fine-tuning workloads, including GPU memory management, batch sizing strategies, distributed execution constraints, checkpointing, and data pipeline performance in HPC or large-scale compute environments
- Scripting and automation skills (Bash, Python, or equivalent)
- Experience supporting shared infrastructure with uptime and operational responsibility
Additional Strengths
- Experience supporting AI / ML training workloads in production environments
- Experience with parameter-efficient fine-tuning workflows and runtime optimization in shared HPC environments
- Familiarity with foundation model adaptation workflows and large-scale training constraints
- Familiarity with containerized execution environments
- Experience operating multi-tenant compute environments
- Experience with monitoring and observability systems
- Networking fundamentals for high-throughput environments
- Experience collaborating with engineering or deployment teams in production settings
Key Performance Metrics
- Cluster availability and operational stability
- GPU and CPU utilization efficiency
- Workload performance and scheduling effectiveness
- Time required to debug and resolve user issues
- Time required to onboard new workloads and users
What We Offer
- A collaborative environment with engineers and researchers working on real industrial AI deployments
- Direct impact: your infrastructure will run daily AI workloads and production systems
- An office at the epicenter of tech: OGR Torino technology hub
- Competitive compensation and access to advanced computing infrastructure
How to Apply
Submit your application exclusively through the online form:
- Cover letter (max. 1 page) describing how your profile fits this specific position
- CV and optional links to technical projects or operational experience
About Us
The Italian Institute for Artificial Intelligence (AI4I) was founded as a research institute to perform transformative, application-oriented research in Artificial Intelligence, driving innovation and industrial progress. The Institute is designed to engage and empower gifted, entrepreneurial, and ambitious researchers who are committed to generating real-world impact at the intersection of science, technology, and industrial transformation. Competitive salaries, performance-based incentives, access to dedicated high-performance computing resources, state-of-the-art laboratories, and strong industrial collaborations are among the distinctive features that define AI4I. The Institute fosters a dynamic international environment and an ecosystem that supports the creation and growth of innovative startups.
AI4I’s mission is to advance scientific research, technology transfer, and, more broadly, Italy’s innovation capacity, promoting positive impact across industry, services, and public administration. To achieve this, the Institute contributes to building a research and innovation infrastructure that leverages AI methods, with a special focus on manufacturing processes and the broader Industry 4.0 value chain. AI4I also maintains strategic relationships with leading organizations in Italy and abroad, including Competence Centers and European Digital Innovation Hubs (EDIHs), positioning itself as an attractive destination for researchers, companies, and startups seeking collaboration and impact.
HPC / AI Specialist employer: AI4I
At the Italian Institute of Artificial Intelligence (AI4I) in Turin, you will thrive in a collaborative and innovative environment, working alongside top engineers and researchers on cutting-edge AI projects. With competitive salaries, performance-based incentives, and access to state-of-the-art computing resources, AI4I is dedicated to fostering employee growth and development while making a tangible impact in the field of artificial intelligence. The vibrant tech hub of OGR Torino provides a unique backdrop for your career, ensuring that your contributions directly support real-world industrial applications.
StudySmarter Expert Advice🤫
We think this is how you could land HPC / AI Specialist
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like AI4I!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like HPC / AI Specialist at AI4I.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like AI4I.
✨Apply Directly through Our Website
When you find a suitable opening like HPC / AI Specialist at AI4I, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace HPC / AI Specialist
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at AI4I, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at AI4I. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at AI4I
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at AI4I!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
