Top Artificial Intelligence Jobs in Rome

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Build EVE, an open-source Earth Observation AI platform for ESA. Integrate satellite data catalogues, Copernicus services, processing platforms, APIs, imagery, and geospatial tools. Develop agentic pipelines that route queries, orchestrate tasks, call backend services, and generate coherent responses. Design specialized EO sub-agents, support ESA platform integrations, and create tutorials, notebooks, and documentation. The role requires Python, geospatial data engineering, REST APIs, Docker, Linux, and cloud or HPC experience.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Lead global marketing and corporate communications to define Multiverse's narrative, positioning, and GTM for AI/quantum products. Partner with the CEO, build and scale the marketing & communications team, own product messaging, PR, executive positioning, agency relationships, and measure impact on awareness and enterprise pipeline.

Design and deploy AI microservices and LLM-powered applications using Python, REST/gRPC, Docker, and Kubernetes. Build RAG, hybrid search, agent, fine-tuning, quantization, evaluation, and prompt-guardrail systems. Monitor model quality, latency, cost, and security while integrating databases and SIEM/SOC platforms. Establish MLOps, testing, observability, and compliance standards for high-security public-safety environments. Collaborate with security teams on CJIS and FedRAMP audits, with optional travel to Japan and the United States.

Develop and own production-ready machine learning, LLM, NLP, and RAG solutions within Palantir Foundry and AIP. Responsibilities include data exploration, model development, evaluation, deployment, monitoring, workflow integration, and optimization for accuracy, scalability, reliability, latency, and cost. Collaborate with engineers and business stakeholders, make architecture decisions, translate business needs into AI solutions, and communicate model behavior and limitations.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

Owns commercial success, revenue, and strategic relationships for embedded HR technology partners. Responsibilities include managing a $10M+ annual bookings target, developing partner sales motions, enabling partner sellers, driving pipeline and ARR growth, resolving commercial issues, leading executive business reviews, expanding partnerships, coordinating cross-functional teams, and managing partner account managers and embedded sales leads.

Design, build, and ship AI-powered product features from prototype through production. Own architecture, model selection, integrations, evaluation, reliability, cost, and latency. Work across frontend, backend, and infrastructure while establishing reusable AI development practices. Collaborate with engineering and product teams to define requirements, identify risks, and deliver maintainable, monitored, production-ready systems using LLMs, embeddings, RAG, vector databases, and multiple providers.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.

Create narrative-driven, long-form cinematic videos using AI-first workflows, from scripting and prompting through generation, editing, compositing, motion graphics, color correction, and final delivery. Maintain character and scene consistency across sequences, experiment with emerging AI video models, refine production workflows, and independently execute creative direction. The role includes stylized and explicit adult content and requires strong storytelling, technical judgment, rapid iteration, and collaboration.

Creates narrative-driven, long-form cinematic videos using AI-first workflows. Responsibilities include scripting, prompting, generating sequences, editing, compositing, motion graphics, color correction, and final delivery. The role requires maintaining character and scene consistency, experimenting with emerging AI models, refining production workflows, and working autonomously under creative direction. Content may include explicit adult visuals.

Remote role for ML/AI experts to assess AI-generated content, craft and answer advanced technical prompts, evaluate model responses for accuracy, relevance, and clarity, identify errors or hallucinations, and provide feedback to improve AI systems.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Build and iterate AI systems spanning computer vision, image manipulation, video generation, and agentic data analysis. Own the full pipeline from model research and API integration through scalable web application deployment. Develop rapid MVPs using AI-assisted tools, orchestrate multiple models into autonomous workflows, and test solutions in e-commerce operations before scaling them into SaaS products.

Owns planning, activation, optimization, testing, budgeting, and reporting for paid campaigns across TikTok, Meta, and YouTube. Manages $1M+ budgets, presents data-driven recommendations to clients, tracks platform changes, and partners with strategy and creative teams. The role also mentors a Paid Media Executive and establishes team standards for campaign QA, reporting, naming conventions, and optimization practices.

Build hands-on cloud-native training labs and technical courseware using YAML, Markdown, Bash, and Python. Support training platforms, troubleshoot delivery issues, and help design and deliver demos, workshops, and training sessions. Apply instructional design fundamentals, use AI coding agents, collaborate cross-functionally, incorporate feedback, and progressively take ownership of technical enablement content and presentations.

Develop AI applications using Generative AI, LLMs, APIs, SDKs, and RAG techniques. Build prototypes, backend services, scripts, and enterprise integrations using Python or C#/.NET. Experiment with models and prompting, work with Azure AI services, databases, embeddings, and vector search, test existing solutions, investigate issues, document findings, and collaborate with experienced engineers.

Own the AI cost visibility product end-to-end, building Go backend services, APIs, and TypeScript/React interfaces. Translate cloud AI spend and usage data into clear FinOps experiences, while driving architecture, reliability, monitoring, and iteration. Collaborate closely with customers and product stakeholders, use AI throughout the engineering workflow, mentor peers, and shape product direction in an ambiguous market.

Own the AI cost visibility product end to end, developing Go backend services, APIs, data processing, and TypeScript/React interfaces. Translate AI spending data into clear FinOps experiences, work closely with customers and product needs, and use AI throughout the engineering workflow. Lead feature design, implementation, release, monitoring, and iteration while setting engineering standards, mentoring peers, and building scalable cloud-based SaaS capabilities.

Own AI cost visibility features end-to-end, from customer problem discovery and system design through implementation, release, monitoring, and iteration. Build scalable Go backend services, APIs, and TypeScript/React interfaces that process and present cloud AI spend data. Apply AI throughout the engineering workflow, contribute to product direction, understand FinOps and AI economics, mentor peers, and uphold reliable engineering practices.

Build, operate, and improve production services that deliver machine learning models within exocad’s AI Design product. Responsibilities include model serving APIs, containerized deployments, versioning, staged rollouts, rollback automation, infrastructure provisioning with Terraform and AWS, monitoring, observability, and performance tuning. The role also contributes to training and labeling infrastructure and requires collaboration across engineering, product, and global teams, including work across AWS global and China environments.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.