Top Machine Learning Jobs in Hungary

As a Senior Software Engineer II - Fraud Risk, you'll develop payment fraud detection systems using machine learning and collaborate with teams to enhance them.

The Customer Success Engineer will act as a technical expert and advisor, ensuring customers adopt Deepgram's voice technologies effectively, manage customer relationships, conduct demos, and drive growth opportunities.

The EMEA Sales Leader will drive the company's expansion in the region, establish sales pipelines, develop partnerships, and oversee the sales team.

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.

Join Welo Data as part of a global community focusing on data annotation and enhancing AI models with diverse linguistic expertise.

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

Seeking a seasoned data scientist to advance methodologies for cardiovascular health assessment, collaborating with medical experts and algorithmic team.

As a Senior Research Engineer, you will work on applying generative AI models for video production and improving model performance in avatar rendering, utilizing your expertise in post-training techniques.

The S&T Cadet role involves training in product development, simulation and modeling, and digital technology to innovate and improve PPG's coatings. Candidates should have backgrounds in materials science or engineering, and must publish scientific work before graduation.

The Modeling Engineer will develop finite element models for structural, thermal, and materials analyses, run simulations, collaborate with teams, and provide design guidance and documentation.

Lead engineering organizations at Diligent, driving AI-driven product development, cultivating teams, and ensuring ethical implementation of technology.

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

The Head of Master Data Management oversees master data governance and quality, leads MDM initiatives, and implements data standards while driving AI integration across the organization.

Develop and implement machine learning models for lead scoring, customer segmentation, and optimization, while collaborating across teams to drive data-driven strategies.

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

As a Senior Research Engineer, you will manage data lifecycle for researchers, build a human-centric data lake, and enhance model performance through high-quality datasets in an AI-driven environment.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead AI-powered analytics capabilities for customer engagement in pharma launches, collaborating with stakeholders to create data-driven solutions.

The Data Scientist will develop and deploy predictive and descriptive models, collaborate with teams, and analyze data to support business decisions and objectives.

The Senior Quality Operations Engineer will manage quality systems, ensure compliance with regulations, oversee audits, and optimize workflows in medical technology.

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.

Lead the Core & MLOps Squad to build and maintain scalable infrastructure for data services, ensuring MLOps excellence and team mentorship.

Manage a portfolio of customers, ensuring they maximize value from Sardine's fraud prevention and compliance products while collaborating with internal teams and analyzing performance metrics.

Manage IT projects, coordinate teams, ensure stakeholder satisfaction, track resources, and facilitate agile development while mentoring team members.

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