Top Machine Learning Jobs in Hungary

Build and optimize agentic AI capabilities for clinical outcomes assessment workflows, including retrieval-augmented generation, semantic search, model orchestration, prompt architecture, evidence synthesis, recommendation generation, and evaluation. Develop secure, explainable, evidence-backed AI systems using scientific, clinical, regulatory, and internal data. Collaborate with scientists, product teams, engineers, security, legal, and commercial stakeholders while documenting model behavior and supporting responsible AI governance.

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.

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.

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.

Analyzes complex datasets, develops and deploys machine learning models, cleans and preprocesses data, and creates visualizations and reports. Presents actionable insights and strategic recommendations to clients and stakeholders, collaborates with cross-functional teams, researches emerging techniques, and mentors junior data scientists.

Interns support PPG’s digital transformation and research projects across artificial intelligence, software development, physical rendering, analytical science, and materials science. Responsibilities may include data analysis, model development, web application development, 2D/3D rendering, chemical experiments, instrument operation, laboratory reporting, data integration, and technical research. Interns receive expert mentorship and are expected to collaborate effectively, solve problems, follow safety and quality standards, and commit to at least six months when possible.

Leads complex global finance transformation projects, including cost accounting, operations finance, S/4HANA ERP transformation, and business divestiture workstreams. Responsibilities include project governance, stakeholder alignment, risk management, executive reporting, organizational change, controls compliance, and process improvement. The role also evaluates AI and machine learning opportunities to improve finance reporting and insights, while coordinating cross-functional teams across Finance, IT, Operations, and Product Data Management.

Leads global finance transformation projects focused on cost accounting, operations finance, ERP migration, standard costing, data governance, controls, and OCOGS reporting. Manages stakeholders across Finance, IT, Operations, and Product Data Management; supports change management, testing, issue resolution, process improvements, and AI-enabled reporting. Develops team members, advises senior leadership, and coordinates projects across Thermo Fisher business groups. Requires less than 25% domestic and international travel.

Leads technology strategy, engineering teams, platforms, and external partners across Legal, Risk, Compliance, Digital Trust, and Safe & Secure. Drives AI-native product development, cloud and SaaS adoption, responsible AI practices, security, privacy, governance, and scalable architecture. Builds high-performing global teams, manages technology ecosystems, aligns technical initiatives with business objectives, and communicates effectively with senior stakeholders.

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.

Designs, builds, deploys, and maintains production-grade full-stack applications, APIs, services, and user experiences integrating AI/ML capabilities. Provides technical leadership across architecture, development, testing, security, scalability, observability, deployment, and support. Partners with AI/ML engineers, data scientists, product teams, security teams, and business stakeholders to deliver reliable AI-powered applications, establish reusable engineering patterns, resolve technical risks, and mentor engineers.

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.

One-year R&D trainee program at PPG’s Global Coatings Innovation Institute, featuring rotations, training, project participation, mentoring, and presentations. Trainees may specialize in product formulation, simulation and modeling, digital technology and AI, or color science and 3D rendering. The role supports coatings innovation, data-driven development, digital twins, process optimization, and advanced product development, with potential management, technical, or cross-functional career paths.

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.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.

Designs, builds, and evaluates research prototypes and production-ready systems for portable AI agents, model routing, provider interoperability, memory, retrieval, tool use, and multi-agent workflows. Responsibilities include developing evaluation frameworks, conducting statistically rigorous experiments, creating schemas and APIs, optimizing model and agent systems, and translating research into secure, reliable, reusable components. The role collaborates across research, infrastructure, security, product, and engineering teams and communicates findings through technical reports, benchmarks, demonstrations, open-source releases, and publications.

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.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own the full enterprise customer journey from kickoff through adoption and ongoing value realization. Build executive and technical stakeholder relationships, lead QBRs and EBRs, translate product performance into business outcomes, manage risks and escalations, provide strategic ecommerce recommendations, maintain success plans, and partner with Account Management on retention and expansion.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

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.