Top Artificial Intelligence Jobs in Lisbon

Lead and manage high-performing teams developing ML/AI platforms, focusing on LLM infrastructure and collaboration across departments.

You'll develop specs and workflows, implement quality standards, and improve data pipelines while collaborating with teams throughout the delivery lifecycle.

The role involves developing data pipelines, designing evaluation workflows, supporting presales and project delivery, and improving client implementations.

The AI/ML Engineer will develop AI-driven solutions, analyze data, and build production-grade systems, utilizing Python and relevant ML techniques.

The AI Solutions Manager drives strategy and commercialization of AI solutions, focusing on scalable solutions, partnerships, and sales enablement.

Lead AI initiatives for Data Intelligence product, managing the product lifecycle and collaborating across teams to deliver AI solutions.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

This role involves architecting and building AI agent systems, developing full-stack features, and shaping the technical direction of an early-stage startup's AI platform.

As an AI/ML Specialist Solutions Architect, you will design scalable AI solutions, manage AI deployments, and collaborate with clients to enhance customer satisfaction.

The AI Automation Consultant will drive automation initiatives using Microsoft Power Platform, engaging with stakeholders to design and deliver AI-enhanced solutions and optimize workflows.

The Senior DevOps Engineer will design, implement, and optimize ML/AI pipelines using Azure Databricks, ensuring AI models are production-ready and scalable.

The role involves building AI-driven products, designing intelligent workflows, and developing data pipelines for efficient AI integration and automation.

The role combines designing AI/ML architectures and hands-on engineering on AWS. Responsibilities include client requirements gathering, cloud architecture design, and implementing CI/CD for AI workloads.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

As a Senior Site Reliability Engineer, you will enhance the reliability and performance of our inference platform, leveraging Kubernetes and Terraform while ensuring smooth scalability of systems under load.

As an MLOps Engineer, you will architect and build scalable infrastructure for AI models, ensuring reliability and automation throughout the entire lifecycle of production AI systems.

As an AI Email Marketing Specialist, you will execute and automate email campaigns, manage segmentation and A/B testing, and implement AI tools for marketing efficiency.

Lead the LLM team at EverAI, focusing on architecture, training, and deployment of models for AI companions. Responsibilities include coding, model lifecycle management, and developing high-precision moderation systems.

WunderGraph seeks a Staff FullStack AI Engineer to lead architecture for AI-driven projects, mentoring engineers and ensuring scalable, secure systems. Responsibilities include backend and frontend development with a focus on AI workflows and enterprise readiness.

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

The Lead AI Engineer will architect and deploy scalable multi-agent AI systems, manage operationalization and memory integration, and develop CI/CD pipelines while influencing technical directions and mentoring teams.

Drive revenue growth and expand Kaltura's presence in AI solutions for designated verticals. Manage sales cycles, develop GTM strategies, and collaborate across teams to enhance market penetration.

Lead the LLM team to architect, train, and deploy AI models, optimizing real-time user experiences and creating advanced moderation systems.

Lead a team of researchers to develop advanced AI systems, focusing on multimodal models and engaging user experiences. Responsibilities include mentoring, driving research direction, and collaborating with engineering to deploy innovative features.

Applied AI Engineers will define and deliver AI systems for clients, shape AI visions, build products, and advance the core product using real-world data.