Top Machine Learning Jobs in Portugal

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

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.

Design, build, and operate production AI systems including LLM agents, retrieval pipelines, event intelligence, and real-time inference services. Own architecture, orchestration, evaluation, guardrails, observability, reliability, and cost optimization at scale. Partner with platform, product, and research teams, and provide technical mentorship while developing resilient distributed systems for high-volume event streams.

Build and ship production AI systems, including LLM agents, retrieval pipelines, event intelligence, tool integrations, and inference services. Contribute code, tests, observability, evaluation, and monitoring for high-volume real-time systems. Collaborate with platform, product, and applied-research teams while learning to optimize latency, throughput, cost, reliability, and model quality through mentorship and code reviews.

The Product Definition Analyst will document business flows, gather requirements, assist in solution design, and support testing for biometrics solutions in airport systems.

Develop complex cloud applications and scalable infrastructure for the Altium 365 platform. Build distributed, high-load systems and platform features involving APIs, databases, microservices, authentication, caching, messaging, search, and multi-tenancy. Perform performance profiling, optimization, load and stress testing, influence architecture across teams, and establish engineering standards, best practices, and technical governance.

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.

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.

As an AI Product Manager, you will lead the development of AI-powered features, collaborating with cross-functional teams to align products with user needs and business goals, while overseeing the product lifecycle.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

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 product strategy and execution for AI-enabled insurance products. Define 6–12 month direction, own P&L-impacting programmes, embed experimentation and AI playbooks, mentor PMs, and partner across engineering, data science, design, legal, and leadership to deliver measurable commercial outcomes.

You will solve complex problems related to cross-border logistics and B2B systems, focusing on high-load architecture and AI-driven tools.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Join the AI engineering team to develop reliable AI infrastructure for manufacturing systems, focusing on MCP servers, telemetry, and model retraining pipelines.

Own the Subscriptions roadmap end-to-end: research, prioritize, coordinate cross-product dependencies, drive features through delivery, and enable sales and documentation to maximize retention and revenue.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

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.