Top Machine Learning Jobs in Budapest

Lead a team of engineers in developing AI capabilities, managing projects and ensuring high-quality work while fostering a positive culture.

Lead engineering projects in data acquisition, curate multimodal datasets, develop scalable data pipelines, and conduct experiments for insights in AI.

As a Software Engineer Intern, you will build features for user-facing products, design data pipelines, implement scalable services, and contribute to technical documentation while being part of a collaborative team.

As a Machine Learning Engineer II, you will build and enhance ML models to identify fraud, collaborate with teams, and communicate results effectively.

As a Senior Data Scientist at Chaos Labs, you'll enhance modeling capabilities and deliver insights for decentralized finance, collaborating with engineering and product teams.

The Senior AI/ML Engineer at Nansen will develop AI models for blockchain data analysis, collaborating with teams to enhance platform capabilities and mentor junior engineers.

The Senior Sales Engineer will support technical sales efforts, deliver demos, and provide a consultative role to potential customers, focusing on data labeling solutions for AI systems.

Design and deploy LLM applications for payroll, lead architecture decisions, and collaborate with teams. Requires AI/ML experience.

Lead a team of engineers to develop and deploy innovative ML solutions, focusing on LLMs and AWS Cloud services, while overseeing the ML lifecycle and fostering team growth.

Research and develop AI/ML models for handwriting recognition and related technologies, collaborating with a multidisciplinary team to deliver innovative features.

As a Senior Software Engineer, you'll create advanced AI systems to improve developer productivity, integrate existing tools, and mentor junior engineers.

Lead the development of ML solutions for knowledge curation, optimize data pipelines, drive research initiatives, and mentor team members.

The role involves building and iterating machine learning models, collaborating with stakeholders to address Trust & Safety issues, deploying models in production, and improving team performance through knowledge sharing and documentation.

The Robotics ML Engineer will build AI-first robotics projects and data pipelines, create educational content, and interact with customers to improve projects at Rerun.

The ML Research Engineer will develop and deploy computer vision algorithms, mentor junior engineers, and collaborate across teams to enhance item authentication solutions.

The role involves deploying and maintaining machine learning pipelines, developing retrieval-augmented generation systems, and optimizing model performance, requiring extensive experience in ML Ops and software engineering.

As a Senior Cloud Architect, you will architect, deploy and manage AI/ML cloud solutions while mentoring team members and optimizing workflows.

As a Senior Cloud Architect, you will architect, deploy, and manage cloud-based AI/ML solutions, leveraging AWS technologies and providing consultative support to clients.

The Senior Cloud Architect will leverage cloud technologies to address customer needs, focusing on AI/ML solutions while mentoring team members and enhancing personal brand through thought leadership.

Lead Machine Learning Engineering projects using Databricks. Collaborate on AI/ML solutions, engage with clients, and drive innovation.

Lead and mentor teams on machine learning projects, focusing on computer vision and systems architecture. Drive technical decisions and optimize existing models for performance and reliability.

Lead a team developing AI solutions focusing on computer vision and generative AI, integrating ML into production workflows, and ensuring ethical practices.

As a Middle/Senior ML Engineer, you will design and improve ML models, collaborate with teams, maintain models in production, and drive innovation in ML and AI solutions.

Lead a team of engineers in developing and deploying machine learning solutions utilizing LLMs and AWS, while managing project roadmaps and team dynamics.

Lead a team of engineers to develop ML solutions, focusing on LLMs and AWS cloud. Oversee projects, manage resources, and ensure technical execution.