Top Machine Learning Jobs in Naples

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.

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 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.

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.

Build Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

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.

Develop, validate, deploy, and maintain machine learning solutions for medical device manufacturing and CAD/CAM systems. Build deep learning and multimodal AI models using computer vision, 3D geometry, meshes, images, and structured data. Integrate models into production systems, conduct performance analysis, maintain ML workflows, and translate research into practical manufacturing applications while collaborating with engineering, manufacturing, and product teams.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Designs and delivers production credit analytics and machine learning platforms for regulated financial-services clients. Responsibilities include architecture, Python and SQL development, reproducible ML workflows, MLOps, data quality, model governance, Snowflake application reliability, monitoring, access control, and technical leadership. The role works directly with clients and modelling specialists to productionize credit-risk models, support multiple portfolios, and evaluate responsible uses of LLM-assisted analytics.

Designs, builds, and maintains scalable data and machine learning infrastructure, pipelines, databases, integrations, self-service tools, and MLOps workflows. The role includes platform expansion, observability, security, data quality, performance optimization, infrastructure as code, CI/CD, documentation, and collaboration with data scientists, analysts, and stakeholders. Strong experience with cloud platforms, Kubernetes, containerization, databases, big data, orchestration, and AI-assisted development is required.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.