Top Machine Learning Jobs in Budapest

Leads Pfizer’s enterprise applied AI strategy, architecture, governance, operating model, and transformation efforts. Drives portfolio-level technical decisions, reusable capabilities, standards, and measurable business outcomes. Provides hands-on architecture and code review using modern AI and agent frameworks while leading engineers, contractors, and vendors. Oversees quality, security, performance, spending, and technical direction, mentors technical leaders, and evaluates emerging technologies and industry trends.

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.

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.

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

Lead Cost Accounting and Operations Finance projects, drive S/4 Hana ERP transformation for divestiture, manage a small team, enforce governance and data standards, validate controls and automate processes, influence senior stakeholders, and implement AI/automation to improve reporting and analysis.

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.

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.

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.

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.

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.

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.

Lead the estimating product roadmap for an AI-powered construction SaaS: prioritize and ship MVPs, run rapid experiments, conduct user discovery with estimators, define success metrics, and iterate using data and user feedback.

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.

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.

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.