Top Machine Learning Jobs in Italy

Intern will develop AI-enabled tools for NAND memory cell characterization, including waveform ingestion, preprocessing, feature extraction, reference comparison, reporting, and human-in-the-loop validation. The role involves collaborating with cell engineers, testing and refining tools, documenting modules, and applying AI to improve analysis workflows. Candidates should understand AI/ML fundamentals, Python or C/C++, signal processing, and time-domain waveforms. Familiarity with NAND operations, LLM orchestration, waveform libraries, and oscilloscope formats is preferred.

Lead and develop machine learning, LLM, and automation projects using large-scale network and device telemetry. Clean and transform data, engineer features, build models for anomaly detection, forecasting, and optimization, and deliver reproducible analyses with Python and SQL. Collaborate with engineering and product teams to deploy, integrate, and monitor models in production while contributing to MLOps workflows.

Supports management consulting projects in the banking sector through process analysis, organizational modeling, business cases, benchmarking, research, and project deliverables. Participates in client meetings, project management activities, technology trend research, and internal consulting initiatives. The role requires banking knowledge, strong analytical skills, Microsoft Office proficiency, English, and willingness to travel in Italy and abroad.

Supports management consulting projects in banking through business process analysis, organizational model design, project management, analytical modeling, benchmarking, business cases, and preparation of client deliverables. Participates in client meetings, technology research, and initiatives involving FinTech, Generative AI, robotics, and Machine Learning. The role requires English fluency, banking knowledge, and willingness to travel internationally and work at client sites.

Leads Italy’s end-to-end demand planning and S&OP processes for the ice cream and frozen food business. The role develops forecasts, aligns Sales, Marketing, Finance, and Supply Chain, monitors forecast accuracy, optimizes inventory and service levels, minimizes waste, and implements demand planning technologies including Kinaxis. It also manages collaboration with service providers and motivates a cross-functional team.

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.

Own the vision, roadmap, commercialization, and executive strategy for Kaltura’s AI-powered learning and enablement platform. Lead 0-to-1 MVP delivery and post-MVP expansion across AI course generation, conversational tutoring, personalized learning, simulations, and enterprise foundations. Integrate acquired products and agentic AI capabilities while partnering with engineering and GTM teams on architecture, pricing, packaging, positioning, and enterprise sales. The role requires deep B2B SaaS product leadership, enterprise learning platform experience, production AI/ML delivery, and strong technical and commercial judgment.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

Own the strategy and execution of integrated B2B marketing campaigns for enterprise AI solutions and a self-service platform. Drive pipeline, product adoption, acquisition, and category awareness through ABM, content, events, paid media, lifecycle, social, partnerships, PR, and sales activation. Coordinate internal teams and agencies, optimize messaging and conversion paths, and measure performance across account engagement, pipeline, product adoption, and awareness.

Supports clients with AI-enabled risk management and business process transformation. Responsibilities include process analysis and redesign, requirements gathering, AI use-case development, process mining, automation, business intelligence dashboards, control framework alignment, operating model design, implementation support, testing, change management, and client presentations. The role also mentors junior consultants and contributes to internal methodologies and thought leadership.

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.

Design and deliver internal systems, Go services, APIs, data models, dashboards, visualizations, and LLM-powered workflow features. The role includes writing specifications, estimating work, code reviews, testing, documentation, security, performance, accessibility, and collaboration with nontechnical stakeholders. The engineer will handle sensitive people data, mentor colleagues, and improve team practices in a globally distributed environment.

Own the anti-fraud product roadmap across signup, payments, account protection, compute-abuse prevention, risk scoring, manual review, customer verification, and appeals. Partner with Trust & Safety, Engineering, Data Science, Analytics, and Legal to define detection rules, models, incident responses, experiments, and compliance processes. Monitor fraud losses, chargebacks, false positives, review throughput, and detection speed while minimizing customer friction.

Own and improve production machine learning pipelines focused on accuracy, efficiency, and trustworthiness. Build LLM evaluations, judges, datasets, metrics, and benchmarks; run experiments across prompts, models, and pipeline designs; and reduce LLM costs through smaller task-specific models. Expand anonymization capabilities, evaluate open-source models, and collaborate with quality engineers to ship reliable ML features. Document findings and communicate technical trade-offs clearly.

Lead the technical direction and early development of video-based computer vision systems for retail action recognition. Design end-to-end data and ML pipelines, manage video annotation workflows, train and deploy production models, optimize precision, recall, and latency, and provide technical leadership while collaborating with product and engineering stakeholders.

Lead a virtual pharmacology modeling program using complex biological datasets. Assess data and proposals, build pipelines and machine learning proof-of-concept models, identify data gaps, collaborate with laboratory scientists, establish scientific validation, and prepare models for internal use and future commercialization. The role requires reproducible, documented code and models, clear communication with technical and non-technical stakeholders, and may expand to team leadership.

Lead and develop Customer Success Managers across Southern Europe, especially France and Spain. Ensure enterprise customers successfully launch and derive measurable value from the product, build executive and technical stakeholder relationships, translate product capabilities and performance data into business outcomes, establish scalable customer success processes, and handle complex escalations.

Develop quantitative models for sports pricing, odds compilation, and risk management. Analyze large datasets, identify trading insights, deploy models with engineers, monitor performance, conduct back-testing, and continuously improve model accuracy. Collaborate with data scientists and engineers to align models with business needs. The role requires Python, sports betting market knowledge, statistical modeling, and experience with odds and margin optimization.

Manage 28+ CIO and senior IT leader relationships, develop customized service plans, deliver executive briefings and workshops, facilitate events, and collaborate with sales to drive member engagement and renewals. The role requires extensive technology leadership, consulting or CxO experience, multilingual fluency, large transformation program experience, CIO-level IT knowledge, and executive sales or business development skills.

Develop and deploy machine learning models for retrieval, reranking, indexing, search relevance, crawling, and content understanding. Build large-scale embedding and retrieval systems, evaluation pipelines, and quality metrics for agent-native search. Integrate models into high-throughput production services while balancing latency, quality, and cost. Collaborate on architecture and product decisions involving search, retrieval, and LLM-based systems.

Lead product marketing for the French market by developing localized positioning, messaging, sales enablement, launch campaigns, and customer insights. Partner cross-functionally with product, sales, marketing, engineering, design, communications, and partnerships teams. Track adoption and market performance, identify growth opportunities, and lead product marketing strategy for a major Paris customer event. The role requires French and English fluency, B2B technology marketing experience, and travel within France and internationally.

Own the end-to-end strategy, roadmap, and outcomes for a network intelligence and security product serving ISP customers. Partner with engineering, data science, security, and compliance teams on architecture, ML evaluation, privacy, and production delivery. Conduct customer discovery, analyze market and threat trends, define requirements and metrics, build business cases, and represent the product to technical customers, executives, sales, marketing, and public audiences.

Leads Sanofi Italy’s privacy program, including risk assessments, GDPR compliance, data subject rights, breach management, cross-border data transfers, AI and automated decision-making reviews, privacy-by-design, training, audits, regulatory liaison, and vendor oversight. The role partners with senior business, legal, digital, HR, R&D, and commercial stakeholders to enable trustworthy innovation while protecting data subjects and supporting global privacy initiatives.

Build and operate probability-based sports event models for prediction markets, quote two-sided prices, manage inventory and risk, and reprice markets in response to news and live events. The role requires strong applied statistics, Bayesian modeling, calibration, data quality controls, and real-money forecasting experience. Work is conducted in-office in Sofia or Milan with participation in an on-call rotation supporting around-the-clock crypto trading systems.