Top Artificial Intelligence Jobs in Italy

Freelance, part-time remote role improving AI-generated Italian content through data collection, evaluation, and annotation. Tasks include pairwise comparisons, counting, object tagging and labeling across audio, video, images, and other collected data. Flexible schedule, long-term project, immediate start.

Design, build and deploy AI-powered solutions (custom copilots, conversational agents, embedded AI) using Microsoft Copilot Studio, Power Automate and Azure AI Foundry. Integrate with Snowflake and enterprise systems, collaborate with stakeholders to define use cases, operationalise models, maintain reliability and governance, and evaluate emerging AI tools.

Lead the design of complex managed service solutions, integrating technology and services to achieve client business outcomes, while participating in the presales process and developing IT strategies.

Design, build, and deploy production-grade agentic AI systems: multi-agent orchestration, RAG pipelines, provider integration, LLMOps (eval harnesses, prompt versioning, observability), cloud-native deployment, client embedding, reusable patterns, and metrics-driven performance/safety reporting to stakeholders.

The Process Engineer will develop AI techniques for image analysis, design software for machine vision, and evaluate algorithms in the Photonics Industry.

Provide hands-on technical leadership for AI/ML initiatives: turn ambiguous problems into production-ready solutions, design systems for predictive maintenance, anomaly detection, time-series forecasting, and large-scale multimodal ML; guide engineering trade-offs, improve quality and reliability, and coordinate across engineers, data scientists, product and domain experts.

Evaluate and test AI chatbots and language models in Italian via structured written and voice interactions. Submit ratings, write-ups, screenshots, or recordings per task specs. Work is task-based, freelance, flexible hours, and requires language and technical assessments plus identity verification.

Intern will develop and test plant process simulation models (LNG, geothermal, heat pumps), apply ML/AI surrogate and reduced-order models for design and operational optimization, support digital development programs, perform data analysis and reporting, learn commercial simulation software, and collaborate with cross-functional teams while following HS&E standards.

Remote internship supporting social media, digital marketing, market research, brand identity, and AI-driven content strategies. Create and schedule posts across major platforms, research AI tools, build Excel databases, update social guidelines, and assist marketing campaigns under mentorship for 15–20 hours weekly (5–6 month minimum).

Remote unpaid internship supporting digital positioning, AI-powered market and competitive research, social media and Google Business optimization, content drafting, and building organized research databases to inform marketing strategy.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

This internship involves completing internal projects, assisting engineers, learning software, and collaborating with teams on design and data analysis tasks.

The Founding AI Full-Stack Engineer will build end-to-end features, work with LLMs, and collaborate directly with founders in a fast-paced startup environment.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

Develop a Python-based AI/data pipeline to parse EDA outputs and PDFs, combine NLP, computer vision, LLM/LVM and graph methods to map circuit topologies, integrate historical failure data, predict failure modes, generate standardized FMEA reports, and validate the proof-of-concept with hardware engineers on a baseline board.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Build and maintain Kong AI Gateway features (multi-LLM routing, semantic caching, MCP), implement proxying, load balancing, database support, troubleshoot bugs, optimize performance, and integrate with third-party deployment platforms.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Join a client-facing squad as a hands-on Senior Full-Stack Engineer working across Kotlin backends and React/TypeScript frontends. Apply AI-native delivery practices and agent/harness engineering to accelerate delivery, unblock the team, and share patterns across the organisation while using AWS and cloud data tooling.

The role involves designing AI-based financial tools, supporting consulting projects, creating digital learning content, and enhancing advisory activities.

Define, implement, and operate AI governance frameworks to ensure safe, ethical, and compliant AI use. Advise and coach teams, influence senior stakeholders, collaborate with legal, risk, privacy and security, and design lifecycle controls, risk assessments, approvals, audits, and monitoring. Translate technical AI concepts into policy, drive continuous improvement, and support enterprise AI standards and assurance.

Own and scale AI enablement: build core orchestration, LLMOps/MLOps platforms and governance, integrate generative AI into product, optimize cost/latency, run PoC-to-production delivery, upskill teams, standardize tooling and vendor strategy, and track adoption/ROI metrics.

Build and test AI-agent features and internal agent frameworks for a proactive cybersecurity platform. Implement and integrate generative AI systems (agents and RAG), stay current with AI research, and apply innovations to product development and evaluation within a security-focused environment.