Top Machine Learning Jobs in Hungary

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

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Leads digital transformation across procurement by implementing and optimizing SAP, Coupa, ERP, e-sourcing, and supplier management technologies. Oversees data governance, integration, process improvement, category and spend analytics, supplier performance monitoring, and cross-functional project delivery. Evaluates emerging capabilities such as AI and RPA, manages stakeholder relationships, mentors team members, and drives procurement technology innovation and operational efficiency.

Build Solidgate’s new ML/AI function, developing production machine learning models, recommendation systems, and real-time transaction-routing decision systems. Own experimentation from ideation through A/B testing and deployment, engineer features from high-cardinality transactional data, integrate emerging AI technologies, and collaborate with Product, Engineering, and Data Platform teams on training and analytics pipelines.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

Own machine learning projects from exploration through production, building reliable agentic LLM systems for clinical settings. Develop evaluation datasets, offline and online testing harnesses, LLM-as-judge workflows, regression tests, and production feedback loops. Improve models through prompting, retrieval, distillation, and fine-tuning. Partner with product, clinical, and engineering teams, while reviewing code, sharing knowledge, and mentoring junior engineers.

Develop machine learning solutions for extracting information from digital and scanned documents across multiple formats. Build prediction, recommendation, data pipeline, and dataset solutions based on business needs and user behavior. Analyze and visualize data, present findings to the team, and build enterprise AI agents using LLMs and related machine learning technologies.

Research and investigate global fraud trends using BioCatch data and external sources. Produce data-driven insights, visualizations, written thought leadership, dashboards, and presentations. Build repositories and automate analysis workflows while applying fraud expertise and AI tools to validate findings and support sales and marketing.

Lead and grow a machine learning engineering team responsible for fraud and risk models. Manage experimentation portfolios, balance research with delivery, evaluate model performance rigorously, and guide work through production release. Partner with Risk, platform, and infrastructure teams to set priorities, improve training and experimentation systems, communicate results, and make autonomous roadmap decisions. The role is a hands-on player-coach requiring technical depth, people leadership, strong communication, and comfort operating under uncertainty.

Lead product vision and discovery for a genomics-driven diagnostic and personalization platform. Validate hypotheses with patients, clinicians, and partners; translate research into product specs; coordinate labs and data providers; partner with engineers and researchers to build AI prototypes; shape data, regulatory, and GTM strategy while making core product and architectural decisions.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Lead and scale enterprise Automation and AI across GBS Shared Services. Define strategy, oversee global delivery of RPA, low-code and AI/ML solutions, ensure governance, drive ROI, partner with finance and operations workstreams, build team capabilities, and manage portfolio, budgets, and KPIs.

Design, back-test and implement pricing, risk management, and agency trading strategies; collaborate with developers to integrate models into the trading platform; participate in product ideation, modeling, parameter tuning, and risk evaluation.

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.

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

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

The Staff Software Engineer will lead technical design and delivery for ABBYY Vantage platform, mentor engineers, improve platform health, and influence architectural decisions.

Drive product adoption and customer outcomes via 1:1 and 1:many channels. Onboard and support scale customers, manage escalations, monitor health indicators, collaborate cross-functionally, run webinars and calls, prioritize high-volume tasks, and help mitigate churn while identifying expansion opportunities.

Design, build, deploy, and own production-grade machine learning systems for a proactive AI platform. Responsibilities span data curation, model training, evaluation, inference, monitoring, troubleshooting, optimization, and continuous iteration at scale. The role translates research into reliable products, balances latency, cost, safety, and performance, and collaborates with research, engineering, and product teams. It also includes mentoring engineers, conducting code reviews, and independently driving complex initiatives from concept through launch.

The role involves designing and developing model evaluation pipelines, user studies for subjective evaluations, and automated dashboards to report results, alongside leading the evaluation team and communicating with other teams to improve model performance.

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

Develop, validate, deploy, and maintain machine learning features that automate orthodontic treatment planning. Responsibilities include decomposing business needs into ML problems, building deep learning models for 3D meshes, text, and tabular data, analyzing model performance, collaborating on production architecture and integration, researching scientific advances, and transferring technology across product teams.

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