Top Machine Learning Jobs in Budapest

The Account Executive will drive new business by selling SaaS solutions to Managed Service Providers in the Nordics, managing the full sales cycle, and achieving revenue targets.

As a Senior AI Engineer, you'll architect and deploy AI solutions on GCP, transform AI experiments to production, and conduct training sessions.

Responsible for project delivery within an IT solution area, managing teams, ensuring customer satisfaction, and improving team dynamics.

The AI Solution Architect will design AI and ML solutions, oversee pre-sales processes, create project estimates, and validate proposals, ensuring technical accuracy and client engagement.

Manage end-to-end big data, cloud, and machine learning projects, ensuring success by meeting objectives, budget, and deadlines while enhancing customer satisfaction.

Responsible for leading technical execution of AI solutions, ensuring quality and readiness. Oversee engineering practices and collaborate with teams for integration and deployment.

Lead AI and machine learning architecture, mentor teams, drive innovation, and evaluate tools for AI systems development across global teams.

Lead the modernization of C++ Computer Vision library, design algorithms for Intelligent Document Processing, and mentor engineers.

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

Lead and manage complex AI-driven projects in the HR domain, collaborating with diverse teams to deliver scalable enterprise applications and solutions.

Perform remote data tasks to improve AI-generated Hungarian content, including data collection, evaluation, annotation, pairwise comparisons, counting, and object tagging across audio, video, images, and collected data.

The Senior Data Scientist will lead projects, provide consultancy in data science and AI, develop internal solutions, and mentor team members while ensuring customer success.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The AI Scientist analyzes complex datasets, develops AI-driven methodologies, collaborates on research projects, and communicates insights in healthcare.

Lead enterprise AI and data strategy, design GenAI solutions for banking, guide C-level stakeholders, define product vision and roadmaps, oversee implementation, and enhance AI offerings and go-to-market strategies.

The Senior Applied Data Scientist will develop and validate learner modeling, ensuring outputs are trustworthy and ready for product use, while collaborating with various teams.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

The Machine Learning Engineer II builds production ML models to detect fraud, collaborates on engineering teams, and improves the commerce protection platform.

The Senior AI/ML Engineer will design and implement AI/ML solutions, lead project discussions, mentor junior staff, and provide technical guidance in a cloud environment.

As an Applied ML Engineer, you will build and scale data pipelines for video generation, ensuring data quality and optimizing preprocessing workflows.

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.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.

Lead the Applied AI Team in developing and deploying ML systems for clinical care, mentoring engineers, and driving initiatives across the AI stack.

Own and drive ML solutions for clinical care at scale, including LLM fine-tuning and production deployment, collaborating across teams.