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.

Leads analytical methodology and evaluation for AI-based healthcare and pharmaceutical workflows. Owns model selection, cohort and HCP segmentation, agent decision logic, and evaluation frameworks. Partners with engineering, data architecture, and governance teams to productionize rigorous analytical methods, identify new data and techniques, communicate insights, and mentor data science and engineering colleagues.

Leads data science methodology and advanced analytics for AI-enabled Medical Affairs workflows. Develops and evaluates statistical, machine-learning, NLP, and AI models using healthcare and real-world data; defines validation, monitoring, and decision frameworks; partners with engineering, governance, and business teams to operationalize solutions. Provides technical leadership, mentorship, documentation standards, and strategic guidance while ensuring privacy, compliance, responsible AI use, and clear communication of analytical findings.

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Develops CAD tools, flows, and methodologies for analog and digital circuit simulation and verification in NAND memory design. Collaborates with design, verification, layout teams, and EDA vendors; provides user training, documentation, and support. Implements AI-assisted and agentic automation workflows to improve design efficiency, quality, and pre-silicon outcomes.

Provides staff-level technical leadership for enterprise AI/ML platform infrastructure. Designs and operates AWS, Kubernetes, serverless, and containerized environments; develops infrastructure-as-code, CI/CD, observability, security, governance, and cost-optimization standards. Supports generative AI workloads, model routing, reliability, scalability, and performance. Partners with engineering, security, and operations teams, mentors engineers, reviews architecture, and drives platform maturity across multiple teams.

Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.

Leads strategic SEO initiatives across technical optimization, content, off-site SEO, search intent, and generative search optimization. Uses analytics and visualization tools to develop insights, recommendations, and performance reports. Integrates SEO with broader digital marketing, UX, CRM, CRO, and technology strategies across countries. Manages consultants, projects, deadlines, and client delivery while applying HTML, CSS, JavaScript, CMS, SEO tools, and AI/ML capabilities.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

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.

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.

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.

Designs, develops, operationalizes, and maintains enterprise-scale data applications, pipelines, and workflows for structured and unstructured data. Collaborates with analysts, developers, engineers, and data consumers in an agile environment to build analytic solutions supporting mission-driven clients. Responsibilities include data retrieval, parsing, processing, assessment, design, implementation, and maintenance.

Conduct deep learning research for multimodal foundation models across language, Earth observation, and cardiology. Design neural architectures, implement and evaluate experiments using large-scale GPU and HPC resources, benchmark state-of-the-art methods, guide junior researchers, coordinate research partners, and organize publications and open-source releases.

Develop data-driven solutions for enterprise customers and internal teams, including exploratory analyses, statistical models, machine learning, forecasting, experiments, dashboards, and data products. Translate ambiguous business challenges into measurable analytical problems, collaborate with engineering and product teams on deployment, communicate findings to technical and non-technical stakeholders, and measure business impact across translation quality, operations, customer behavior, marketing, and financial performance.

Develop analytical and machine learning solutions for consulting clients across industries. Responsibilities include designing solutions, building prototypes, evaluating model effectiveness, explaining data science concepts to clients, and collaborating with colleagues globally. Projects involve NLP, credit risk modeling, portfolio decarbonization, promotion analytics, GenAI validation, supply chain risk, and customer churn modeling.

Creates and manages global demand plans for optical products, monitors orders against forecasts, identifies supply chain risks, improves demand planning accuracy, and leads demand review meetings and complex planning projects. The role applies statistical and analytical forecasting methods, interprets large datasets, coordinates with markets and cross-functional stakeholders, and develops actions addressing excess inventory, obsolescence, lead-time, supply capability, and financial risks.

Leads enterprise AI transformation programs from strategy and roadmap development through implementation, adoption, governance, and value realization. Coordinates budgets, vendors, resources, metrics, risk management, and responsible AI policies while partnering with executives and cross-functional teams. Drives organizational change, AI capability building, user adoption, and scalable innovation across international business entities.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Supports consulting clients by designing analytical solutions, developing machine learning and statistical models, building prototypes, validating AI tools, and communicating complex data science concepts. Projects span financial services, risk management, sustainability, retail, supply chain, and customer analytics. The role involves close collaboration with colleagues and clients, continuous technical learning, and occasional international travel.

Provides technical leadership for digital transformation within infrastructure and engineering. Develops and improves automation, dashboards, data analytics, AI-enabled applications, and integrated digital tools. Translates business needs into scalable solutions, coordinates developers and technology providers, supports governance and cybersecurity compliance, drives adoption through training and change management, monitors solution performance, and mentors contributors.

Own end-to-end talent acquisition and headhunting for Arago’s technical hiring across France, North America, and Israel. Partner with the CEO, CTOs, and engineering leaders to define roles, source and close senior engineers, scientists, and technical leaders across hardware, optical, software, and research. Build proactive sourcing pipelines, improve interview processes and hiring standards, monitor pipeline health and hiring velocity, and communicate progress to leadership.

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.

Monitor Borsa Italiana markets in real time and retrospectively, focusing on derivatives, trading rules, liquidity obligations, market interventions, alerts, investigations, and suspicious transaction reporting. Support market participants, maintain surveillance processes, and contribute to algorithms and AI-based tools for detecting unusual trading patterns and automating routine monitoring tasks. The role is office-based in Milan and may require extended working hours.