Top Machine Learning Jobs in Lisbon

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.

Designs and operates scalable production data infrastructure for high-volume athlete, sensor, and time-series data. Builds streaming ingestion, graph models, low-latency ML feature systems, evaluation and monitoring infrastructure, and multi-tenant architectures. Ensures data provenance, lineage, observability, reliability, and correctness while collaborating with ML engineers, data scientists, sport scientists, and domain experts. Requires expertise in Python, SQL, streaming technologies, AWS, graph data modeling, causal inference, AI evaluation, and telemetry systems.

Design, build, and operate production machine learning systems for personalization, recommendation, and send-time optimization. Own the full model lifecycle from experimentation and feature engineering through distributed training, deployment, monitoring, and online testing. Build scalable data pipelines and model-serving architectures with Databricks, Spark, AWS, Ray, and Kubernetes. Partner with platform teams, improve infrastructure, mentor engineers, and guide technical direction for machine learning at Iterable.

Build and deploy production machine learning systems for classification, retrieval, ranking, personalization, and evaluation. Develop efficient models and pipelines, improve search relevance and personalization, monitor production performance, debug issues, and ship measurable quality improvements while balancing accuracy, latency, cost, privacy, and reliability.

Build and deploy production machine learning systems for AI-native applications. Responsibilities include classification, retrieval, ranking, personalization, model evaluation, embedding-based search, fine-tuning, and training, inference, and deployment pipelines. The role emphasizes improving accuracy, relevance, latency, cost, and reliability; monitoring production performance; debugging issues; and using real-world feedback to drive measurable model improvements.

Drive enterprise sales growth for IQVIA’s AI-powered pharmacovigilance and drug safety technology across EMEA. Responsibilities include prospecting, developing strategic accounts, managing the full sales cycle, exceeding quotas, engaging senior safety stakeholders, and collaborating with product, consulting, hosting, and managed services teams. The role requires experience selling complex SaaS, technology, consulting, and managed services solutions to pharmaceutical, biotech, medical device, and clinical research organizations, with strong knowledge of drug safety and pharmacovigilance.

Design and deliver cloud-based AI/ML systems with a focus on database architecture, scalable data pipelines, model training and production, generative and deep learning model customization, HPC algorithm R&D, data preprocessing, storage/retrieval design, and cross-functional infrastructure alignment including edge and HPC resources.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Build and deploy production-ready AI pipelines integrating LLMs and foundation models. Develop scalable GenAI services, transition prototypes into production, implement LLMOps and monitoring, optimize RAG pipelines and vector database retrieval, and explore prompt engineering, fine-tuning, and agentic workflows. Collaborate with data engineers and business stakeholders to deliver AI solutions and communicate technical concepts to nontechnical teams.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Perform multilingual legal data collection, evaluation, and annotation for international business contracts. Analyze clauses, obligations, and terms; participate in onboarding, calibration sessions, and quality reviews; and collaborate within secure client environments to support AI training and evaluation for contract management platforms. The role requires legal or contract expertise, English and Portuguese fluency, and strong contract interpretation skills. Data annotation or machine learning evaluation experience is preferred.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.

Conduct research across the full machine learning lifecycle, including ideation, model design, implementation, evaluation, training, inference optimization, and deployment. Develop novel machine learning methods and foundation models, establish evaluation protocols, scale training with GPUs or TPUs, and improve research engineering infrastructure for rapid experimentation.

Design trusted AI-powered experiences across Intermedia products, including copilots, conversational interfaces, recommendations, automation, and agentic workflows. Lead research, UX strategy, interaction design, prototyping, testing, launch, and optimization. Partner with Product, Engineering, AI/ML, Research, Security, Privacy, and Legal teams; evolve design-system patterns; promote transparency, user control, accessibility, and responsible AI; and mentor designers.

Own the roadmap and end-to-end delivery of an AI product area across Intermedia’s communication products. Conduct customer and stakeholder discovery, define requirements, prioritize backlogs, partner with engineering and UX, and manage Agile delivery. Use product metrics, experimentation, customer feedback, and market insights to guide decisions and improve usability. Communicate progress and risks while aligning cross-functional teams on product priorities.

Design AI-powered user experiences across web, desktop, mobile, and administrative products. Lead UX strategy, research, interaction design, prototyping, usability testing, and post-launch optimization for conversational interfaces, copilots, recommendations, automation, and agentic workflows. Establish trustworthy, transparent, accessible AI interaction patterns and contribute to scalable design systems. Partner with Product, Engineering, AI/ML, Research, Security, Privacy, and Legal teams while mentoring designers and influencing product strategy.

Design and lead trusted AI experiences across Intermedia products, including copilots, conversational interfaces, recommendations, automation, and agentic workflows. Own initiatives from research through launch, creating journeys, prototypes, high-fidelity designs, and design-system patterns. Collaborate with Product, Engineering, AI/ML, Research, Security, Privacy, and Legal teams while establishing transparency, user control, accessibility, and responsible AI practices. Mentor designers and help shape the organization’s overall AI interaction language.

Design trusted, intuitive AI experiences across Intermedia products, including copilots, assistants, conversational interfaces, recommendations, automation, and agentic workflows. Lead initiatives from research and discovery through prototyping, implementation, launch, and optimization. Collaborate with product, engineering, AI/ML, research, security, privacy, and legal teams; contribute to design systems; establish responsible AI patterns; conduct user research and usability testing; and mentor other designers.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Leads demand-side yield strategy across iion’s ad marketplace and owns strategy for Cognitiion, its AI-driven yield optimization platform. Diagnoses marketplace performance, directs Yield Analysts, designs experiments, defines optimization metrics, and converts findings into platform requirements. Partners with marketplace, commercial, data science, engineering, and AI leadership to improve revenue, efficiency, bidding, win rates, and traffic allocation.