Top Artificial Intelligence Jobs in Budapest

The Senior AI Compute Infrastructure Engineer will manage and optimize GPU and accelerator clusters for AI workloads, collaborate with teams, and ensure reliable performance and cost efficiency.

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

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.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Lead AI architecture and implementation for financial services clients: support business development, enable and manage engineering teams, design scalable LLM/multi-agent systems, ensure AI safety, compliance, and monitoring, and translate business needs into technical specifications.

This role involves owning the architecture and delivery of LLM systems, optimizing ML workloads, mentoring team members, and designing AI solutions tailored to client needs.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

The Principal Engineer will lead the design and delivery of core platform capabilities, focusing on scalable systems, AI application, and mentoring engineers while driving architectural decisions and improving operational systems.

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.