Top Machine Learning Jobs in Hungary

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 the Weaviate Database product: own roadmap and strategy, translate customer and research insights into features across schema, storage, replication, and search quality, coordinate cross-functional teams, drive developer adoption, and measure feature outcomes post-release.

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.

Develop, design, test and implement imaging and 3D reconstruction algorithms using C++ and Python. Analyze real data, optimize for high-performance computing, integrate algorithms into applications, and collaborate across algorithms, physics, and electronics teams while participating in design and code reviews.

Design, develop, and maintain high-performance, secure Java backend services and APIs. Ensure reliability, scalability, and cost-efficiency across microservices, databases, messaging systems, and capacity planning. Troubleshoot, profile, benchmark, and optimize systems (including ML applications) and collaborate with Kazakhstan stakeholders.

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.

Lead product strategy and roadmap for query interpretation and search quality. Own models, tools, and metrics to optimize recall and precision. Collaborate with ML, infra, and product teams, triage quality issues, benchmark competitors, and build evaluation frameworks and explainability for search results.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.

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 and develop AI-driven features to enhance customer experience, execute ML projects, and optimize AI performance while collaborating cross-functionally.

Responsible for SAP CO operations and improvements, project management, change management, and cross-functional collaboration in an international IT Finance team.

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.

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

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.

The Factory Software Engineer will implement technology solutions for data integration, collaborate with stakeholders, and ensure delivery of high-quality software solutions.

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

Combine and prepare data from multiple sources, clean and validate datasets, perform analysis and exploratory data work, and build/test machine learning models in Python. Translate business questions into analytics tasks, present insights to technical and non-technical stakeholders, and collaborate across teams to support reporting and decision-making.

Design, prototype, and productionize specialised LLMs by working with model weights, attention mechanisms, and efficient architectures. Build reusable Python libraries, run experiments and evaluations, and deploy models on GPU-accelerated AWS infrastructure (SageMaker/EC2/S3). Contribute to research-to-production lifecycle, maintain evaluation frameworks, optimize infrastructure for cost and velocity, and collaborate on the team's research agenda while mentoring junior engineers.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop and optimize vision-language models, managing the full model lifecycle from training to deployment, focusing on efficiency and innovation in multimodal architectures.

Lead design and implementation of multimodal and computer-vision ML systems for Intelligent Document Processing. Architect scalable solutions, optimize model performance, ensure production readiness, and mentor engineers while driving technical standards and delivery.

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.