Top Artificial Intelligence Jobs in Budapest

Manage influencer campaigns end to end across multiple brands and markets. Responsibilities include creator casting, briefing, negotiation, contracting, campaign timelines, budgets, approvals, client communications, performance tracking, reporting, and optimization. The role requires using CPV and campaign KPIs to manage commercial outcomes, ensuring content meets brand and compliance requirements, and operating as a power user of Kyra’s platform and AI tools.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

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.

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.

Build AI agents using large language models, tool-use frameworks, and SAP Business AI capabilities. Develop and deploy machine learning models as scalable production APIs on SAP’s Business Technology Platform. Validate agent use cases through proof-of-concepts, measuring accuracy, latency, cost, and safety. Explore emerging AI technologies, follow Agile software development practices, and participate in design, coding, testing, and production releases as part of a global team.

Lead end-to-end data science and AI/ML projects, translating client objectives into technical solutions and contributing to pre-sales discussions. Develop machine learning, deep learning, NLP, LLM, and generative AI solutions using cloud platforms and modern frameworks. Collaborate cross-functionally to integrate models into products, while providing technical leadership, mentorship, and guidance on scalable, production-ready AI applications.

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.

Build and maintain LLM-powered platform services, APIs, and AWS infrastructure for educational products. Responsibilities include designing scalable backend systems, managing prompts and context, enabling auditing and response processing, creating developer tooling and documentation, establishing AI best practices, and collaborating with feature teams. The role emphasizes secure, performant, maintainable code, API design, distributed systems, and effective code reviews.

Work with the CTO and Product Managers to identify inefficient product-development processes and build AI-powered workflows, automations, prototypes, and internal tools. Evaluate their impact, connect information across existing tools, document successful solutions, and explore new AI approaches. The role requires analytical problem-solving, experimentation with AI or automation, process improvement, communication with technical and non-technical colleagues, and independent work.

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.

Lead Kraken Pro’s social media strategy across X, Telegram, and other platforms. Create platform-native content, react quickly to crypto and trading trends, manage the content calendar, engage the community, translate product updates into compelling narratives, track performance, and optimize through experimentation. Partner with Legal and Communications to ensure accurate, compliant messaging across regions.

Leads multiple agile engineering teams building AI-first governance, risk, and compliance products. Responsibilities include owning technical roadmaps, driving scalable distributed systems on AWS, championing AI and automation, partnering cross-functionally, and mentoring engineers. The role requires extensive software development and people leadership experience, along with expertise in cloud infrastructure, CI/CD, DevOps, and agile practices. Preferred experience includes modern web technologies, serverless AWS architecture, infrastructure-as-code, data integration, application security, and regulated environments.

Lead Chainguard’s European government affairs and public policy strategy across the UK and Europe. Engage regulators, governments, standards bodies, and industry coalitions; develop policy positions and consultation responses; translate cybersecurity regulations into product, positioning, and customer implications; and establish a scalable policy function. The role requires senior stakeholder engagement, technical policy communication, frequent regional travel, and eventual team-building responsibility.

Leads the global HR technology and digital transformation strategy, including the transition from Workday to SAP SuccessFactors. Oversees HR technology governance, AI adoption, automation, analytics, data quality, digital workflows, employee self-service, and enterprise transformation programs. Builds and leads a high-performing digital HR function, develops organizational capability, drives adoption, and partners with senior HR, IT, and business leaders to deliver measurable improvements in HR efficiency, employee experience, and decision-making.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

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.

Lead design, development, and deployment of scalable AI-powered customer-support automation, including Java microservices, Kafka pipelines, intent detection, routing, RAG, LLM workflows, and AI-agent integrations. Build solutions with AWS Bedrock, improve platform reliability and performance, collaborate on conversational experiences, and mentor engineers.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

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.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.

Serve as the founding customer-facing engineer for Kimchi, leading product demonstrations, customer workspace setup, inference API integrations, model routing optimization, and governance policy implementation. Configure agent workflows, integrations, budgets, cost attribution, and access controls. Translate customer feedback into product improvements while identifying opportunities for revenue expansion. The role combines hands-on LLM and inference expertise with customer enablement and commercial thinking in a remote-first environment.

Produce photorealistic AI-generated visual creatives for performance marketing campaigns across paid media and landing pages. Create lifestyle, human, and product imagery; enhance source photos; develop creative variations; and iterate based on performance data. Collaborate with marketers, copywriters, and editors while maintaining brand consistency, visual quality, realism, and production readiness. Research emerging AI tools and improve workflows to support conversion-focused testing and scalable creative output.

Supports business operations through data organization, analysis, process improvement, automation, AI experimentation, troubleshooting, and data quality checks. The intern will use tools such as spreadsheets, AI assistants, APIs, and workflow integrations to reduce manual work and improve operational efficiency. The role also involves communicating with colleagues, investigating issues, following established processes, and identifying practical improvements.

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.