Top Machine Learning Jobs in Budapest

Build and improve scam prevention infrastructure, including backend and frontend detection systems, financial crime controls, and scalable web applications. Own projects end to end, primarily focused on backend development, while operating distributed systems and CI/CD pipelines. Design resilient database schemas, optimize queries, maintain high code quality through test-driven development, and collaborate with Product, Data Science, and Investigations teams to protect customer funds.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own the architecture and production delivery of LLM, RAG, agentic, and classical machine learning systems. Design scalable AI solutions on Databricks using Spark and MLflow, optimize latency, cost, reliability, and performance, and implement evaluation, monitoring, CI/CD, rollback, and versioning. Translate client needs into end-to-end architectures, lead technical decisions and pre-sales discussions, and mentor team members on GenAI and ML best practices.

Data Scientist Intern supporting AI data quality and analytics for autonomous driving. Responsibilities include using agentic AI and data mining tools to improve training datasets, investigating annotation and pipeline issues, developing Python analyses, and collaborating with machine learning engineers to improve training workflows and efficiency.

Supports cross-functional engineering teams on a Level 4 autonomous trucking project. Responsibilities include coordinating engineering processes, analyzing software delivery issues across the machine learning pipeline, improving collaboration and execution, and experimenting with LLM-based tools. The role requires familiarity with software engineering, machine learning, and Agile processes, plus ongoing university studies in Hungary and English fluency.

Leads end-to-end testing, regression cycles, and release-readiness assessments for agentic and workflow-driven HR GenAI tools. Coordinates testing across product, engineering, governance, risk, and business stakeholders; maintains test frameworks, evaluation criteria, documentation, defect tracking, and risk indicators. Partners with control teams to ensure GenAI capabilities meet monitoring, oversight, data quality, and operational risk standards as models, prompts, and system architectures evolve.

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 Solidgate’s ML/AI function from the ground up, developing real-time payment routing models and production pipelines. Own the full ML lifecycle from experimentation and A/B testing through deployment, while solving modeling challenges involving large-scale transactional data. Partner with Product, Engineering, and Data Platform teams to deliver measurable improvements in conversion, approval rates, losses, and revenue.

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.

Lead and grow the Money & Risk engineering team responsible for fraud prevention, risk scoring, reconciliation, settlement, and chargebacks. Own technical direction for scalable, auditable, secure payment systems across 80+ countries. Drive architecture, engineering standards, AI-assisted development, hiring, coaching, and cross-functional delivery with Product, Data, Finance, Compliance, and Operations.

Lead the software engineering team’s daily operations, technical direction, architecture, reliability, planning, delivery, hiring, and leadership development. Partner with Product, Core ML, and Hardware teams to scale cloud services and deployed checkout devices internationally. Improve monitoring, release processes, testing, incident response, and AI-assisted development practices while balancing customer needs and long-term strategy.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

Develop machine learning and analytics solutions using large-scale datasets. Responsibilities include feature engineering, predictive modeling, workflow optimization, customer implementations, production deployments, stakeholder collaboration, technical training, and resolving data-related challenges. The role requires Python, PySpark, machine learning pipelines, MLflow or Airflow, statistical modeling, and strong communication skills, with preferred experience in fraud detection, risk analytics, compliance, cloud environments, and model monitoring.

Build and maintain internal machine learning platforms, distributed data processing solutions, reusable tooling, and large-scale data pipelines. Improve system reliability, performance, automation, and maintainability while collaborating with data scientists and engineers to productionize machine learning solutions. Contribute to architecture and engineering practices, and mentor teammates.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Manage export sales orders from compliance and documentation through delivery and billing. Responsibilities include export license verification, customs support, order blocking and modification, intercompany automation monitoring, stock allocation, backorder management, logistics coordination, and continuous process improvement. The role requires SAP and Excel expertise, international trade knowledge, order-to-cash experience, strong analytical and problem-solving skills, and fluent English plus German or Dutch.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

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.

Lead the strategy, roadmap, and evolution of Stewardship Intelligence, a corporate governance and capital-markets data product. Manage Product Management and Research teams, improve dataset quality and coverage, introduce automation and AI, and partner with Engineering and UX to deliver product experiences and data services. Engage institutional investors, governance professionals, advisers, and issuers while collaborating with Commercial, Marketing, Sales, and Customer Success on positioning, launches, adoption, and customer value.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

Lead backend development of a scalable, enterprise-grade document management system using Java and Google Cloud. Responsibilities include designing and implementing cloud-based products, optimizing code and data structures, scaling distributed systems, troubleshooting production issues, refactoring for multi-cloud deployment, conducting code reviews, mentoring engineers, and guiding clients and technical teams. The role emphasizes AI-assisted development, disciplined verification, technical leadership, and collaboration across international teams.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.