Top Machine Learning Jobs in Lisbon

Lead product ownership and project management for innovative banking tools and company culture initiatives. Define product vision, roadmaps, budgets, and requirements; coordinate business, engineering, design, and data science teams; oversee project plans, risks, resources, timelines, and quality; monitor product performance and user feedback; communicate progress to senior management; and apply knowledge of AI technologies to product development.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Lead cross-functional teams of machine learning engineers and data scientists, driving technical direction and fostering a collaborative environment to develop high-quality ML-driven capabilities.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Build and scale MLOps infrastructure that moves machine learning models from development to production. Responsibilities include model serving, automated training and deployment, CI/CD, monitoring, drift detection, rollback mechanisms, streaming feature pipelines, and agentic workflow integration. The role requires collaboration with data science, platform, and product teams to deliver reliable, observable, low-latency ML systems.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Lead prompt engineering initiatives, coach and support business users on AI tools, create best practices and training, evaluate AI platforms, mentor junior staff, and document technical learnings to integrate AI into workflows.

Design, develop, and maintain Entrust's iOS SDK for document capture. Implement camera capabilities, on-device image processing and ML, integrate RESTful APIs, improve CI/CD and test automation, collaborate with product and design to deliver accessible, high-quality SDK features across devices.

The RPA Analyst/Developer will design, develop, test, and implement RPA robots, ensuring reliability and quality while continuously improving development practices.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

Seeking a dotnet Engineer with 2+ years of experience in dotnet core, proficient in OOP, SQL, and ideally SPA frameworks like Angular or React. Role focuses on innovative development practices within a remote-first work environment.

The role involves working on high-quality, reliable, and scalable software solutions using various programming methodologies and technologies. You will embrace Agile practices and contribute to the company's mission to improve systems and deliver value to clients.

Embed with engineering clients to own full-cycle technical hiring for software, AI/ML, infrastructure and data roles. Run deep intakes, headhunt passive candidates, coach hiring managers on interview design and calibration, build hiring foundations, report on pipeline health, and use/builder recruitment AI agents to scale impact.

Build, deploy, monitor, and optimise production-grade agentic and LLM systems to detect and prevent risk and fraud. Design agent orchestration, RAG pipelines, and LLM serving while writing production-quality Python, querying large structured datasets with SQL, and implementing ML evaluation, observability, and graceful degradation.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

Design, build, deploy, and maintain production-grade machine learning systems for a proactive AI platform. Own projects end to end, including data curation, model training, evaluation, inference, monitoring, troubleshooting, optimization, and continuous iteration. Translate research into reliable systems at scale while balancing latency, cost, safety, and performance. Collaborate with research, engineering, and product teams, mentor engineers, and provide rigorous technical reviews.

Own and grow the RateHawk Selections product: define strategy and roadmap, run fast experiments, prioritize opportunities from data and research, align Product/Engineering/Commercial/Operations, and co-own delivery to drive measurable revenue.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

Implement and support Microsoft Customer Insights projects: integrate data sources, configure unified profiles, build customer segmentation and behavioural analyses, develop and execute test strategies, connect Customer Insights with Dynamics and other Microsoft platforms, support Sales alongside Corporate IT/T2D, and create dashboards using Power BI.

Drive application security and regulatory compliance through vulnerability management, CI/CD and Azure-based practices, security scanning, compliance testing (DR, pen tests), and developer best-practice governance. Report on product compliance, lead technical change (GenAI, FinOps), and support remediation and patching efforts.

Develop, deploy, and maintain scalable AI/ML pipelines and production models, including LLMs and generative AI. Optimize model performance, latency, and cost across AWS, GCP, and Azure. Apply MLOps practices such as CI/CD, versioning, monitoring, logging, and maintenance. Collaborate with data scientists, software engineers, solution architects, and cross-functional teams to integrate AI capabilities into products and workflows.

Lead client engagements, translate business problems into analytics and ML solutions, provide project oversight, develop presentations, identify new opportunities, and mentor junior team members while orchestrating the team.

Lead design and adoption of the Operations Target Operating Model, govern and deliver Ops improvement initiatives (including automation and AI), quantify and track cost-to-serve impact, coordinate multi-stakeholder M&A and growth activities, and produce COO-ready strategic outputs. Own KPI frameworks, initiative prioritization, and enablement of automation/AI use cases while coaching associates and ensuring TOM adoption across Operations.

Lead a product vertical end-to-end for a neobank superapp: define strategy, roadmap, and acceptance criteria; shape technical design for money movement, reliability, and compliance; apply and evaluate AI/LLM features; coordinate engineering, design, compliance, ops and finance to ship secure, auditable financial products.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.