Top Machine Learning Jobs in Italy

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

Lead professional services business development by positioning Workday as a platform for business transformation. Advise customers on AI, Extend, and Prism-driven solutions, align with Global SIs, run consultative discovery, negotiate and close services agreements, manage pipeline and forecasting, and build executive-level relationships to drive value-based outcomes.

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.

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.

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

Support client deployments of Emiri by triaging issues, identifying root causes, coordinating fixes, coaching commercial teams, configuring and QA’ing client models, testing releases, and surfacing product enhancements via user feedback.

Support engineering projects to design and introduce new pharmaceutical products, packaging, and automation/robotics solutions. Collaborate with departments and suppliers, contribute to Industry 4.0 initiatives, and drive process efficiency and innovation at the Latina manufacturing site.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead and scale a regional Market & Customer Intelligence program across EurAsia, turning market and customer insights into actionable, AI-enabled analytics and decision-ready narratives. Own rollout roadmaps, governance, intelligence cycles, stakeholder enablement, KPI tracking, and cross-functional adoption to embed the capability as a trusted enterprise asset.

Lead development and productionization of TTS and voice-generation systems: train, fine-tune, evaluate models, deploy and optimize for inference, latency, scaling, monitoring, and reliability; translate research into production and define technical direction while collaborating with research, engineering, and product.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

Lead legal counsel for an adtech company providing commercial, product, privacy, and regulatory counsel. Negotiate complex agreements, advise on global privacy and IAB standards, support product launches and AI use cases, manage data governance and incident response, oversee corporate compliance and outside counsel, and build scalable legal operations and contract workflows.

As a Fraud Data Analyst, you will design real-time fraud strategies, develop rules to combat fraud, optimize decision-making, and collaborate with teams to enhance user experience and report performance metrics.

The Fraud Data Analyst designs real-time fraud detection strategies, optimizes decision-making tools, analyzes payment fraud, and presents data-driven insights to leadership.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.

Support ~25–30 learners in a virtual ML/data program by answering questions, facilitating breakout rooms, holding office hours, grading submissions, monitoring Slack, reviewing materials, and providing constructive feedback. Provide bilingual (German/English) technical support focused on data annotation, labeling QA, and generative AI concepts. Participate in onboarding, weekly staff meetings, and submit program improvement write-ups.

The Greenlake Specialist drives sales of aaS and Private Cloud solutions, collaborates with account teams, negotiates deals, and builds relationships with clients, particularly at the C-level, while leveraging extensive industry knowledge and cloud technologies expertise.

Analyze large and varied customer and business data to build ML/statistical models (CLTV/propensity), prepare and integrate datasets, design analysis environments/databases, run hypothesis tests and data mining, generate actionable CRM insights, present findings to stakeholders, and support relationship-marketing initiatives.

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.

Lead the QA engineering team, focusing on automating testing through AI, managing CI/CD pipelines, and ensuring product quality across systems.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.