Top Machine Learning Jobs in Portugal

Join Cloudflare Research as a 12-week fall intern to work on systems-scale problems in security, privacy, and performance. Responsibilities include engineering, data analysis, protocol design, implementation, measurement, and open-source contributions. Projects may span AI/ML, distributed systems, trusted execution environments, cryptography, and networking protocols.

Lead organization-wide software and AI engineering strategy, design scalable cloud-native systems, drive deployment and data integration best practices, and deliver rapid prototype-to-production solutions. Own LLM and ML strategy including model fine-tuning, RAG, AI evaluation, and observability. Mentor technical leaders, shape developer experience and knowledge management, and represent engineering at executive and industry levels.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Lead delivery of cloud-based data engineering, BI and advanced analytics solutions. Advise clients, design solution architectures, build data platforms on Microsoft Fabric/Databricks, develop ETL/ELT pipelines, and create Power BI dashboards. Lead and mentor teams, manage projects end-to-end, and integrate ML/Generative AI into analytics products.

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.

Lead cross-functional projects from planning to delivery, improve operational processes, analyze budgets and KPIs, create internal communications, and introduce AI and automation to increase team efficiency and engagement.

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

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Design, develop, and deploy production-ready AI solutions for insurance, focusing on agentic AI, multi-agent systems, LLMs, RAG pipelines, and computer vision. Research and implement state-of-the-art models, take prototypes through production, collaborate with data scientists and engineers, and contribute to proprietary insurance-focused AI models and scalable international AI products.

Design intuitive, accessible mobile and web interfaces with strong interaction design, prototyping, and illustration. Translate customer feedback and business goals into user flows and localized experiences. Collaborate with cross-functional teams using modern design tools to deliver high-quality UX/UI for international audiences.

Design, develop and deploy machine learning and deep learning (including genAI) models to improve credit risk data quality. Perform EDA, feature engineering, model evaluation, automation, and collaborate with stakeholders to translate business needs into data-driven solutions while ensuring regulatory compliance and coordinating monitoring committees.

Own and improve the technical CRM ecosystem: ensure stability and performance, optimize data flows and automation, redesign templates and components, support campaign execution, and partner with Engineering, MarTech, and Data Science to enable tracking, integrations, and ML-driven experiments while mentoring the CRM team.

Drive end-to-end product development for iTero 3D imaging systems by translating clinical needs into software requirements, leading cross-functional agile teams, driving ML diagnostic initiatives from PoC to productization, analyzing clinical usage data for improvements, and embedding customer feedback into product decisions to enhance usability, performance, and clinical value.

Design, build, and maintain enterprise-grade UiPath automations including orchestration, exception handling, monitoring, security, and integrations. Translate architectures into reusable frameworks, review code, troubleshoot across environments, collaborate with architects and DevOps, and mentor junior engineers while supporting delivery planning and technical client discussions.

Design, build, and maintain enterprise UiPath automations including orchestration, exception handling, monitoring, security, and integrations. Translate architectures into reusable frameworks, review code, troubleshoot issues, mentor engineers, and support delivery in Agile environments.

Lead positioning, messaging, and go-to-market for FineReader and ABBYY's Document Parser/SDK. Drive developer ecosystem strategy, technical content, enablement, and GTM alignment while gathering market intelligence to inform product and growth priorities.

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.

Design, develop, and deploy generative AI models for business use cases. Collaborate with business and technical teams to identify AI opportunities, conduct research on generative AI advancements, and integrate innovations into production solutions.

Lead Vegetation Intelligence product, owning roadmap from ML detection models to customer-facing risk products. Advance detection models, integrate outputs into outage and ignition risk, run user research, and translate model capability into actionable B2B products used in the field.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead and scale a regional Market & Customer Intelligence program across EurAsia, turning market and customer insights into actionable, AI-enabled analytics and decision-ready narratives. Own rollout roadmaps, governance, intelligence cycles, stakeholder enablement, KPI tracking, and cross-functional adoption to embed the capability as a trusted enterprise asset.

Lead development and productionization of TTS and voice-generation systems: train, fine-tune, evaluate models, deploy and optimize for inference, latency, scaling, monitoring, and reliability; translate research into production and define technical direction while collaborating with research, engineering, and product.