Top Machine Learning Jobs in Hungary

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.

Join the Fraud Handling team to automate fraud investigations, improve tooling, and optimize workflows, focusing on customer experience.

Dragonfly is seeking Software Engineers for various portfolio companies, focusing on crypto technologies. Engineers of all experience levels are needed across multiple stacks.

Graduate R&D training program developing talent for coatings innovation across product formulation, simulation (CFD/DEM/FEA, Aspen) and digital science (big data, ML, digital twins). Candidates will support materials and process development, modeling, and AI-driven data platforms. Requires research output, strong problem-solving, communication, and willingness to travel.

The Senior AI & Data Consultant will design AI strategies, advise executives, oversee AI tool adoption, and help grow AI services, primarily within the banking sector.

As an Engagement Manager, you'll ensure customer success in protein R&D by building relationships, tracking metrics, and leading cross-functional teams. You'll manage enterprise accounts and advocate for customers while aligning their needs with Cradle's offerings.

Lead development and productionization of TTS and voice-generation systems: train, fine-tune, evaluate models, deploy and optimize for inference, latency, scaling, monitoring, and reliability; translate research into production and define technical direction while collaborating with research, engineering, and product.

Lead legal counsel for an adtech company providing commercial, product, privacy, and regulatory counsel. Negotiate complex agreements, advise on global privacy and IAB standards, support product launches and AI use cases, manage data governance and incident response, oversee corporate compliance and outside counsel, and build scalable legal operations and contract workflows.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

Lead and grow multiple small, high-output engineering teams focused on AI-powered vulnerability management. Stay hands-on with architecture and code reviews, drive hiring and career development, ensure technical excellence, and coordinate cross-team priorities to deliver customer and revenue impact.

Support ~25–30 learners in a virtual ML/data program by answering questions, facilitating breakout rooms, holding office hours, grading submissions, monitoring Slack, reviewing materials, and providing constructive feedback. Provide bilingual (German/English) technical support focused on data annotation, labeling QA, and generative AI concepts. Participate in onboarding, weekly staff meetings, and submit program improvement write-ups.

Own Go-To-Market for performance media buyers: build relationships, close and onboard clients, represent Kayzen at industry events, advise prospects on product strategy, and funnel market feedback across teams.

As an AI Solutions Architect, you will design scalable AI architectures, evaluate technical feasibility, define product requirements, provide mentorship, and assess AI models for enterprise deployment.

Lead design and management of taxonomies for Non-Financial Risk, collaborating with stakeholders to develop categories supporting semantic search, knowledge graphs, recommendation engines and ML/NLP capabilities. Implement taxonomy governance and change management, perform concept/entity extraction and metadata modeling, and support regulatory and financial data requirements across the Legal & Compliance function.

Lead the development of a strategic analytics roadmap for R&D Procurement, translating business needs into data strategies and fostering team excellence.

Lead development and deployment of ML/DL image-analysis models to optimize orthodontic manufacturing and quality. Integrate models into production pipelines, refactor C++ to Python, build C# UI, work with PLC hardware, validate training results, and transfer technology across product groups.

The Data Scientist will design algorithms for insights, structure data, collaborate with machine learning engineers, and analyze datasets to improve workflow automation and product value.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

The Customer Value Architect will engage with customers to ensure the effective adoption and value realization of the Neara platform, focusing on ROI metrics and customer relationships.

The Customer Success Manager will onboard and support Portuguese utility accounts, ensuring effective use of digital twin technology and driving long-term partnerships and customer satisfaction.

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

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

The role focuses on creating and implementing Data & AI strategies, advising executives, and managing projects to drive AI adoption and business growth.

Lead delivery of software and infrastructure IT projects: manage risks, budgets, change control, stakeholders and reporting; run Agile ceremonies; prioritize backlogs with product owners; coach and motivate project teams; align with governance and ensure stakeholder satisfaction across international engagements.

Perform end-to-end data science for clinical and preclinical studies focusing on wearable and physiological data (accelerometry, EEG, ECG). Design experiments, clean and analyze data, develop signal-processing and ML/AI pipelines, collaborate with clinicians and statisticians, and produce reports and novel analytic tools to support disease understanding and patient-focused endpoints.