Iot Systems Engineer - Security & Applied Ai
Pubblicato il 25-08-2026 - Nessun nome in Torino
At Mulini SRL we are looking for a talented and motivated IoT Research/Software Engineer to join our team. In this role, you will bridge the gap between cutting-edge research and real-world systems, working at the intersection of systems engineering, security, and applied AI for the Internet of Things. You will design, build, and evaluate robust systems that push the boundaries of what's possible while maintaining a strong security posture. See mulini.eu for our current projects and products.
Responsibilities
Design and develop scalable, reliable systems that incorporate AI models into production environments
Identify, analyze, and mitigate security vulnerabilities and mitigation strategies in IoT pipelines, related AI models, and infrastructure
Collaborate cross-functionally with research scientists, software engineers, and product teams
Contribute to threat modeling and security reviews for IoT systems
Publish findings, write technical reports, and present work to internal and external stakeholders
Stay current with the latest developments in IoT security, adversarial ML, and security research
What We Offer
Opportunity to work at a high-impact, cutting-edge startup
Collaborative and intellectually stimulating environment
Competitive salary, equity,
and benefits
Flexible work arrangements (Turin Italy/Hybrid)
Conference attendance and publication support
We are an equal opportunity employer and welcome applicants from all backgrounds.
Requisiti richiesti
Required Qualifications
B.S./M.S./Ph.D. in Computer Science, Electrical Engineering, or a related field
Strong foundation in systems engineering principles (distributed systems, OS internals, networking)
Solid understanding of security principles — network security, IoT security, threat modeling, and vulnerability analysis
Proficiency in Python and at least one systems-level language (C, C++, Rust, or Go)
Preferred Qualifications
Experience with adversarial machine learning, model robustness, or AI safety
Experience deploying and maintaining ML models in production
Hands-on experience with applied ML frameworks (e.g., PyTorch, TensorFlow, JAX)
Prior research experience with publications in top-tier venues (NDSS, USENIX, IEEE S&P;, CCS, etc.)
Experience with cloud security (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes)
Riferimenti per la candidatura
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