Top Machine Learning Jobs in Italy

The Generative AI Engineer will define strategies for Generative AI, design and build innovative products, and mentor engineers, focusing on AI transformation for financial services clients.

As an intern in the Data & Analytics team, you will collaborate on projects using data science techniques to solve client challenges, developing prototypes and engaging in discussions to deliver impactful results.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Work with traders, asset operators, and developers to analyze electricity market outcomes, improve trading and operational strategies, and drive customer success. Translate market workflows into product requirements, collaborate with engineering to enhance analytics, dashboards, and optimization models, and lead customer onboarding, implementation, and ongoing technical account management.

Design, develop, and maintain production ML services and AI agents; extend agent capabilities and hybrid human-expert workflows; implement observability for agent quality and system reliability; collaborate across ML and engineering to deploy and operate LLM-based features in production.

Work on client-facing data science and analytics projects: design analytical solutions, build and validate ML/NLP/GenAI prototypes, implement models and toolkits, communicate insights to clients, and support cross-industry engagements (financial services, energy, retail, telecom). Collaborate in teams, travel internationally, and contribute to project delivery and client impact.

Work on analytics and ML projects for clients across industries: design solutions, build prototypes, implement models (e.g., NLP, credit risk, GenAI chatbots), present findings, and collaborate with teams and clients. Expect international travel, mentoring, and varied project exposure.

Work on client-facing data science and analytics projects: design analytical solutions, build prototypes, implement models (NLP, ML), validate tools (including GenAI), and present findings. Collaborate across teams, travel internationally, and receive mentoring while contributing to real-world financial services, sustainability, and operations use cases.

Drive AI adoption by identifying and prioritizing AI use cases, developing business cases, collaborating with data and tech teams to implement solutions, facilitating workshops, enabling stakeholder adoption, and ensuring responsible AI governance and value realization across the enterprise.

Write, edit, localize and proofread English-language email and social media copy for Google Nordics/Benelux; create social-first assets, run A/B test variants, collaborate with designers, developers, analytics and audience teams, and maintain brand voice and campaign documentation.

Chloris Geospatial seeks experienced individuals with diverse skills in areas such as forest carbon, remote sensing, machine learning, and software engineering, to support their mission of fostering a sustainable economy.

The Revenue Insights Analyst will analyze data to drive revenue growth, develop actionable insights, and support strategic initiatives through collaboration with cross-functional teams and data visualization.

The AI Product Specialist collaborates with cross-functional teams to develop, launch, and enhance AI-driven healthcare products, ensuring they address customer needs and market demands.

Collaborate with clients to design and implement data-driven solutions, build ML/NLP/GenAI prototypes, develop credit risk and probability-of-default models, analyze datasets, validate analytical approaches, and communicate results to stakeholders while working across teams.

Lead technical delivery and product ownership for enterprise AI solutions: define strategy, translate requirements, lead AI squads across ML, data engineering, and software teams, enforce MLOps and governance, and drive deployment, adoption, and measurable business outcomes.

The AI Lead Product Manager will define and own the product strategy for AI-powered health data, lead product teams, engage with stakeholders, and ensure compliance with regulations.

Drive end-to-end product development for iTero 3D imaging systems by translating clinical needs into software requirements, leading cross-functional agile teams, driving ML diagnostic initiatives from PoC to productization, analyzing clinical usage data for improvements, and embedding customer feedback into product decisions to enhance usability, performance, and clinical value.

Lead positioning, messaging, and go-to-market for FineReader and ABBYY's Document Parser/SDK. Drive developer ecosystem strategy, technical content, enablement, and GTM alignment while gathering market intelligence to inform product and growth priorities.

Analyze large and unstructured customer and business data to build statistical and machine learning models (CLTV/propensity), prepare and integrate datasets, design targeted databases/environments, run hypothesis tests and data mining, and communicate actionable insights to stakeholders to drive relationship marketing initiatives.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Lead end-to-end data science projects, design and deploy ML/AI models in production, translate business problems into analytical solutions, ensure code quality and model governance, mentor junior data scientists, collaborate with stakeholders and engineering to drive measurable business impact and promote responsible AI practices.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

As an Engagement Manager, you'll ensure customer success in protein R&D by building relationships, tracking metrics, and leading cross-functional teams. You'll manage enterprise accounts and advocate for customers while aligning their needs with Cradle's offerings.

This program involves developing and deploying AI models, collaborating with teams, and working on high-impact products in a structured training program.