Top Machine Learning Jobs in Milan

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.

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.

Six-month paid internship in Milan focused on building and deploying AI solutions for financial-services clients. The role combines business analysis, AI and machine-learning engineering, software development, APIs, integrations, cloud deployment, monitoring, and client communication. Interns build prediction models, document-analysis and RAG pipelines, evaluate LLMs and agents, and deliver production applications using technologies such as Python, PyTorch, FastAPI, Azure, and Snowflake. The internship is intended to lead to a permanent Forward-Deployed AI Engineer role.

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.

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.

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 full sales cycle for AI compute services across Europe, including GPU clusters, managed inference, and hybrid infrastructure. Build pipeline, qualify workloads, design solutions with architects, manage enterprise and public-sector sales, close complex technical deals, develop partner motions, and provide customer feedback to product teams. The role combines technical consultative selling, executive engagement, forecasting, RFPs, pilots, events, and revenue ownership, with frequent European travel from Milan.

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.

Design, implement, and maintain highly available data pipelines supporting cybersecurity products. Develop medium to large software features, reduce technical debt, collaborate in an agile team, automate processes, and own user-facing features from inception through release. The role emphasizes full-stack development, data engineering, AI, and NLP, with opportunities to use Python or Ruby, Docker, JavaScript, and React.

Build and manage data architecture, models, and high-volume ETL pipelines for financial crime risk analytics. Ensure data integrity, optimize SQL-accessible data relations, develop feature store capabilities, and design AI-powered workflows for data transformation and exploration. The role also leads cross-functional initiatives, translates technical insights into business actions, and supports governed data ownership within a federated Data Mesh strategy.

Designs data architecture, models, and ETL pipelines for financial crime analytics. Ensures data integrity, high-volume batch processing, and efficient SQL-based data relations. Develops AI-powered agentic workflows, feature store capabilities, and scalable distributed processing solutions. Leads cross-functional initiatives, translates business needs into data improvements, and supports risk decision-making through governed, accessible analytical data.

Lead and grow the Money & Risk engineering team responsible for fraud prevention, risk scoring, reconciliation, settlement, and chargebacks. Own technical direction for scalable, auditable, secure payment systems across 80+ countries. Drive architecture, engineering standards, AI-assisted development, hiring, coaching, and cross-functional delivery with Product, Data, Finance, Compliance, and Operations.

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.

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.

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.

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.

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.

Optimize large-scale ML inference systems for throughput, latency, cold-start time, and cost per token. Tune SGLang, vLLM, and TensorRT-LLM across GPUs and distributed clusters; improve batching, scheduling, KV caching, quantization, weight loading, JIT caching, and multi-node inference. Profile and instrument systems to validate performance gains, eliminate storage and networking bottlenecks, and establish technical direction through reproducible benchmarks and experiments.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.