Top Machine Learning Jobs in Hungary

Build production-grade software and data pipelines for the ID Verification machine learning team. Develop Node.js, TypeScript, and Python services, create versioned training datasets, support ML model packaging and production serving, and translate research prototypes into scalable, tested systems. Collaborate with ML engineers, contribute to technical design and estimation, review code, mentor colleagues, participate in hiring, and ensure sensitive data is handled in compliance with residency and privacy requirements.

Build and maintain production-grade native iOS applications using Swift and SwiftUI. Integrate AI and machine learning features through backend APIs, design resilient real-time interaction patterns, optimize performance and memory usage, collect telemetry, and collaborate with ML and backend teams on architecture and API contracts. Ship and support reliable consumer-facing applications in the App Store.

Lead analysis and visualization of complex datasets to support pricing, product, customer, market, supply chain, inventory, and operational decisions. Develop executive reporting, scalable data models, self-service analytics, and AI-enabled data quality capabilities. Investigate discrepancies, improve processes, define data requirements, and collaborate with global cross-functional teams. Translate complex insights for technical and non-technical audiences while mentoring junior analysts and driving continuous improvement.

Leads complex data acquisition, analysis, visualization, and executive reporting across pricing, products, supply chain, inventory, and business performance. Builds scalable data models, improves self-service analytics and data quality, evaluates AI-enabled analytics capabilities, and translates transactional data into actionable recommendations. Partners with global cross-functional stakeholders, defines analytical requirements, supports process improvements, communicates insights clearly, and mentors junior analysts.

Supports the development, enhancement, launch, and lifecycle management of climate-focused investment products. Responsibilities include writing product specifications, coordinating with engineering, data operations, and research teams, testing features, preparing client-facing materials, supporting RFPs and training, responding to product inquiries, and assisting with roadmap prioritization and revenue sizing. The role requires collaboration with senior product managers, internal stakeholders, client coverage teams, and external clients.

Leads the Grouper product, creating item grouping capabilities such as bundles, add-ons, collections, and variations across digital and physical channels. Defines product vision, strategy, roadmap, OKRs, business cases, and success metrics. Partners with engineering, UX, data science, supply chain, stores, and business teams to deliver customer-focused ecommerce experiences that drive engagement, cross-selling, and upselling. Prioritizes backlogs, influences stakeholders, and navigates complex, cross-functional product development.

Own end-to-end talent acquisition and headhunting for Arago’s technical hiring across France, North America, and Israel. Partner with the CEO, CTOs, and engineering leaders to define roles, source and close senior engineers, scientists, and technical leaders across hardware, optical, software, and research. Build proactive sourcing pipelines, improve interview processes and hiring standards, monitor pipeline health and hiring velocity, and communicate progress to leadership.

Conduct advanced research in artificial intelligence and machine learning, including deep learning, graphical models, reinforcement learning, computer perception, natural language processing, and data representation. Define complex business problems, design and deliver modeling solutions, evaluate model performance, establish scientific and engineering specifications, and build analytical roadmaps. Assess production implementation requirements, improve data capture methods, apply statistical and mathematical techniques, and resolve root causes and process bottlenecks.

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.

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

Design, build, and maintain scalable automated test suites (functional, integration, performance, reliability, security) for cloud-native microservices and ML components. Integrate tests into CI/CD pipelines, operate Kubernetes+Helm deployments in test environments, investigate and resolve issues, and promote testability, observability, and quality across agile cross-functional teams.

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.

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, build, and own scalable backend services, APIs, and high-performance web frontends for an autonomous procurement platform. Improve reliability, security, and performance, implement async task pipelines, and collaborate with product and design. Mentor juniors, participate in code reviews, and leverage AI-assisted tools while shipping iteratively in a globally distributed, async-first team.

Build and evolve large-scale search and discovery systems for Target’s digital and in-store experiences. Responsibilities include developing information retrieval, query understanding, relevance ranking, semantic search, machine learning, APIs, data pipelines, and scalable search infrastructure. The role involves applying software engineering patterns, designing architectures, resolving operational issues, using data to solve business problems, and collaborating with product managers, data scientists, machine learning engineers, and engineering teams.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Design and own learner models powering mastery and progression features. Build datasets, training and scoring pipelines, evaluation strategies, testing, versioning, and production monitoring for models handling sparse, noisy, evolving behavioral data. Partner with learning scientists, product, and infrastructure teams to define targets, assess calibration, uncertainty, fairness, stability, and interpretability, and clearly communicate model behavior and limitations.

Develop and implement CoreMedia-based CMS solutions, integrate Deutsche Telekom services, and contribute to complex software architecture and delivery. Responsibilities include code reviews, performance optimization, troubleshooting, documentation, and knowledge transfer. The role requires Java and Spring expertise, AWS integration experience, REST and SOAP knowledge, familiarity with Git, Jenkins, Docker, relational and NoSQL databases, Node.js, DevOps, and CI/CD practices. Strong German and English communication skills are essential.

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.

Own full-cycle recruiting for technical roles, partner with hiring managers to define roles, source and close candidates, build scalable systems and pipelines, optimize hiring with data, and support a global, remote people team while acting as a culture ambassador.

Lead and build Solidgate's ML/AI function from scratch: define vision and architecture, hire and lead the team, deliver real-time decisioning and recommendation systems, partner with Product/Engineering/Data Platform, run experiments and A/B tests, and translate models into revenue-driving production features.

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.

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

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.