Top Machine Learning Jobs in Portugal

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

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.

Design and build data science solutions using visualization, machine learning, and statistical modeling. Develop algorithms and quantitative methods, integrate structured and unstructured data sources, pilot new tools and techniques, and collaborate across teams to deliver scalable, global solutions that inform business decisions and improve processes.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Implement and maintain security controls, monitor security systems, investigate incidents, analyze threats, and enforce security policies. The role requires knowledge of networks, security protocols, operating systems, spam and malware filtering, phishing prevention, email authentication, and incident response. Candidates should be able to solve problems under pressure, support machine learning data annotation, and continuously update their cybersecurity skills.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Own the vision and strategic roadmap for GoCardless payment-success products powered by AI and machine learning. Translate customer insights into data-driven solutions, partner with data platform teams to build foundational infrastructure, and enable sales and support teams to communicate product value. The role requires shaping technical direction, improving payment performance, solving complex customer challenges, and communicating strategy clearly to executives, stakeholders, and customers.

Designs and delivers data engineering, business intelligence, and advanced analytics solutions for clients. Responsibilities include capturing requirements, modeling and transforming data, designing cloud-based data platforms, implementing ETL solutions, and developing reports and dashboards. The consultant advises clients on data and analytics best practices, translates business needs into technical requirements, and delivers Microsoft-based solutions on schedule and within budget.

Develop and implement artificial intelligence solutions using machine learning, generative AI, and large language models. Translate business needs into scalable AI applications, work with data processing and APIs, evaluate and improve models, and operate within modern cloud environments and Agile teams. Strong English communication and continuous learning are expected.

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.

Develops scalable data science solutions using AI, machine learning, statistical models, and automation to address complex life sciences and business problems. Responsibilities include analyzing structured and unstructured data, managing enterprise data lifecycles, researching novel methods, creating visualizations, translating insights for stakeholders, and collaborating across business functions to support medical and organizational outcomes.

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.

Own machine learning projects from exploration through production, building reliable agentic LLM systems for clinical settings. Develop evaluation datasets, offline and online testing harnesses, LLM-as-judge workflows, regression tests, and production feedback loops. Improve models through prompting, retrieval, distillation, and fine-tuning. Partner with product, clinical, and engineering teams, while reviewing code, sharing knowledge, and mentoring junior engineers.

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.

The Senior FinCrime Product Owner will design and implement a financial crime prevention product, develop strategy, and lead product delivery at Deblock.

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.

Lead a comprehensive assessment and redesign of Tiko's global data function: audit team structures, define target operating model, align data architecture and governance, uplift analyst capabilities, recommend tooling and adoption strategies, and map pragmatic ML opportunities. Deliver actionable roadmaps, capability plans, and stakeholder engagement guidance to transition Tiko to a mature, data-driven operating model.

Lead design and development of scalable front-end applications using React and TypeScript for an AI/ML-powered cloud-native SaaS platform. Collaborate with product, UX, backend, and ML teams to integrate APIs and real-time services, drive front-end architecture, optimize performance and accessibility, and contribute to testing and continuous improvement.

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.

Serve as a bridge between creative teams and engineering to integrate AI (LLMs, RAG, agents) into creative workflows. Prototype and develop AI-enabled tools, work cross-functionally, optimize workflows, mentor teammates, and evaluate emerging technologies for deployment.

Bridge creative and technical teams to integrate AI into creative workflows: prototype and develop AI-driven solutions (LLM fine-tuning, RAG, AI agents), optimize processes, mentor colleagues, and lead projects from concept to deployment.

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.