Top Machine Learning Jobs in Lisbon

Leads the product strategy, roadmap, and scaling of Mastercard’s Global Portfolio Optimization capabilities. Converts analytics and business insights into technology-enabled products, recommendations, and workflows through the Mastercard Intelligence Centre. Defines the organization’s AI strategy, evaluates automation and emerging technologies, develops business cases and KPIs, and guides cross-functional teams through delivery, adoption, and optimization. The role requires strong product leadership, technical fluency, quantitative reasoning, stakeholder management, and the ability to drive outcomes in a matrixed organization.

Research and develop real-time AI algorithms for isolating, extracting, and suppressing sound sources from microphone recordings. Responsibilities include training and evaluating audio models, addressing noise and reverberation, optimizing perceptual quality and computational efficiency, and collaborating with DSP and embedded software teams to deploy models on physical devices. The role also supports patents, conference publications, and novel audio experiences.

Design, build, deploy, and maintain production-grade machine learning features and AI/ML services. Responsibilities include developing data pipelines, APIs, model-serving systems, scalable microservices, evaluation frameworks, monitoring, and observability. The role involves collaborating with product, engineering, design, QA, DevOps, and client teams while owning AI capabilities from discovery through deployment and iteration in AWS environments.

Build and ship reliable full-stack software for high-stakes hospital workflows. Own projects end-to-end across product, machine learning, data pipelines, cloud and on-prem infrastructure. Develop backend and frontend features, APIs, integrations, and database systems while collaborating with product and clinical users. Contribute to prototyping, testing, weekly enhancements, and team culture. The role is remote-first across Europe and the US, with international travel to hospitals required.

Manage end-to-end digital marketing campaign delivery across EMEA for an enterprise SaaS organization. Coordinate assets, localization, approvals, uploads, launches, quality assurance, timelines, dependencies, and stakeholder communications across email, outbound, newsletter, and nurture campaigns. Track performance, produce reports, recommend improvements, and resolve delivery risks while collaborating with regional and central marketing teams.

Design and develop scalable Python applications, backend services, APIs, microservices, and cloud-native solutions for finance and AI platforms. Collaborate with data science teams to operationalize machine learning solutions, optimize performance and reliability, implement testing and CI/CD practices, contribute to architecture decisions, and mentor developers.

Leads cybersecurity strategy, governance, risk management, compliance, identity and access management, cloud and SaaS security, API and application security, incident response, vendor oversight, and security reporting for the IQSIGHT business unit. Coordinates penetration testing, vulnerability management, DevSecOps, and AI security governance while ensuring alignment with GDPR, NIS2, ISO 27001, DORA, and emerging regulations.

Develop and maintain Python- and SQL-based analytical models, ETL processes, dashboards, reports, and data visualizations. Analyze complex datasets, monitor data quality and governance, track business KPIs, and provide strategic recommendations. Lead analytical studies, support process optimization and Lean initiatives, and collaborate with business and technology stakeholders to improve operational efficiency and decision-making.

Lead and build a new platform engineering team responsible for cloud-agnostic deployments across AWS, other public clouds, private cloud, and on-premises environments. Design platform services, internal developer platforms, CI/CD, GitOps delivery, AI/ML infrastructure, observability, reliability, security compliance, FinOps, and automated audit evidence. Hire and develop engineers, establish operating standards, and implement AI agents for infrastructure operations. The role requires hands-on Kubernetes, infrastructure-as-code, self-hosted software, cloud portability, and SOC 2, ISO 27001, and GDPR experience.

Develop agentic workflows and reliable automation for real-time audio machine learning research. Build systems that prepare data, train and evaluate models, run hyperparameter searches, perform regression testing, manage experiments and artifacts, and generate reports. Operate on-premises and cloud GPU infrastructure, connect LLM agents to research tools and resources, and collaborate with audio researchers to create reproducible workflows, dashboards, and observability systems.

Leads the strategy, development, delivery, compliance, and adoption of AI products supporting global clinical operations. Translates clinical challenges into AI use cases, requirements, value propositions, and scalable solutions. Oversees products from concept through MVP, pilots, refinement, and sustained adoption while ensuring privacy, AI governance, and GxP compliance. Partners with clinical operations, technology, data, quality, compliance, and digital teams to deliver measurable improvements in productivity, quality, and clinical development cycle times.

Leads planning, governance, delivery, reporting, adoption, and change management across Novartis’s Global Clinical Operations AI portfolio. Coordinates product roadmaps, risks, dependencies, compliance, value tracking, training, and launch readiness while partnering with Clinical Operations, AI, Data, Digital, IT, and business stakeholders to deliver measurable, compliant transformation outcomes.

Develop and operate complex, cloud-native applications for the Altium 365 platform. Responsibilities include designing scalable distributed systems, APIs, data models, microservices, and platform infrastructure; optimizing high-load systems; and driving architectural decisions, engineering standards, and technical governance across teams. The role uses .NET, AWS, MySQL, Docker, Kubernetes, GitLab, and Jenkins, with opportunities to apply AI and machine learning.

Leads data science and AI initiatives that solve complex business problems across Novartis. Responsibilities include data management, statistical analysis, machine learning, visualization, stakeholder storytelling, technology evaluation, exploratory analysis, project coordination, resource planning, governance, and potentially team leadership. The role also contributes to scientific publications, conferences, and advanced analytics strategy while ensuring quality, ethical, safety, and regulatory standards.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Leads the company-wide engineering organization, technical strategy, architecture, delivery standards, and engineering culture. This hands-on player-coach designs systems, writes and reviews code, manages AWS infrastructure and security implementations, oversees reliability, budgets, vendors, disaster recovery, and technical debt, and partners with product and security leadership. The role also hires and develops engineering managers and architects while delivering secure digital asset and AI solutions.

Develop graduate-level Applied AI courses, including lessons, labs, case studies, assignments, rubrics, readings, and projects. Create practical learning materials covering LLMs, RAG, AI agents, automation, APIs, evaluation, and governance. Collaborate with learning designers and university faculty, revise content through academic review, advise on Applied AI topics, and maintain current, rigorous materials for professional learners.

Lead technical execution for high-volume, mission-critical distributed systems. Design scalable, resilient architectures supporting low-latency conversational experiences, microservices orchestration, real-time machine learning, and AI features. Evaluate engineering trade-offs, optimize systems, modernize monoliths into event-driven architectures, and foster collaborative engineering culture. The role requires strong software development experience, technical leadership, Portuguese fluency, and excellent English.

Own the vision, strategy, roadmap, and delivery for Microblink’s Platform and Know Your Agent products. Lead and develop product managers, partner with engineering, design, sales, marketing, and customer success, and manage product metrics. Serve as the VP of Product’s second in command by running planning, prioritization, roadmap reviews, cross-functional alignment, product operations, escalations, and leadership communications.

Develop AI and machine learning solutions for credit risk data quality, governance, compliance, and process optimization. Responsibilities include exploratory data analysis, feature engineering, model development and evaluation, predictive analytics, and AI application deployment. The role collaborates with international stakeholders to translate business needs into data-driven solutions, support regulatory requirements, facilitate risk monitoring committees, and communicate complex concepts across teams.

Conduct applied research in computer vision, biometrics, face recognition, image quality, and anti-spoofing. Manage the full research lifecycle, including data acquisition, annotation, deep learning model training, experimentation, deployment, and SDK support. Collaborate across research teams, resolve technical challenges, uphold security and quality practices, and contribute to patents, publications, and production-ready machine learning solutions.

Lead applied research in computer vision, machine learning, face recognition, anti-spoofing, and biometric capture. Define research strategy, establish data and model governance practices, develop production-ready AI solutions, ensure compliance with responsible AI and security standards, influence product roadmaps, resolve complex technical issues, publish research, generate patents, and mentor researchers.

Investigate fraud claims, identify first-party, third-party, and account takeover patterns, manage UK liability investigations, communicate with banks and merchants, analyze transaction data using SQL templates, and label datasets to improve fraud rules and machine learning models.

Advise city governments across the Americas on designing, prototyping, and launching digital services. Guide system and data architecture, DevOps, infrastructure, AI and machine learning decisions, rapid prototyping, and end-to-end product delivery. Work hands-on with multidisciplinary teams while coaching clients and influencing technical decisions without direct authority. The role requires senior technical leadership, strong communication, and professional English plus Spanish and/or Portuguese.

Executes document onboarding and database management tasks, labels identification-document data under strict privacy standards, analyzes document performance, troubleshoots issues, tests verification tooling, documents processes, and supports second-line inquiries. The role collaborates with coordinators, Product, Engineering, and other stakeholders while maintaining accuracy, security, and compliance.