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Senior Applied AI Researcher

Discussion
  • End-to-end AI solution ownership from problem definition through prototype validation and production support
  • Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives
  • Independent planning and execution of research, experimentation, and iteration cycles in ambiguous problem spaces
  • Design of AI solutions with a system-level perspective ensuring scalability, maintainability, and sustainability
  • Design and prototyping of LLM-powered solutions including RAG-based systems and agent-like workflows
  • Contribution to defining system behavior, scope, and constraints with attention to quality, robustness, and operational considerations
  • Building and maintaining evaluation frameworks to assess AI system performance
  • Development of quantitative and qualitative metrics, benchmarks, and testing approaches to validate prototypes and track improvements
  • Analysis of existing solutions to identify gaps and drive continuous performance enhancements
  • Collaboration with data scientists, engineers, and product teams to ensure smooth transition from prototype to production
  • Clear communication of methods, assumptions, results, and limitations to technical and non-technical audiences
  • Support of engineering teams during implementation by clarifying evaluation criteria, edge cases, and expected system behavior
  • Serving as a technical authority and mentoring junior data scientists
  • Contribution within an Agile / SCRUM development environment
  • Application of good engineering hygiene in research and prototype code to enable reproducibility and collaboration
  • 6+ years of experience in data science, applied machine learning, or a closely related role
  • Strong mathematical, statistical, and machine learning foundations including probability, statistics, optimization, and model evaluation
  • Proven ability to select, apply, and critically evaluate ML models and algorithms for real-world problems
  • Strong Python skills for analysis, modelling, experimentation, and prototyping
  • Strong SQL skills for data exploration, transformation, and analytical workflows
  • Excellent analytical thinking and problem-structuring abilities
  • Experience using Git for version control and collaborative development
  • Strong English communication skills, both written and verbal
  • Hands-on experience with LLMs including prompt/system design and building real-world applications
  • Experience with RAG systems including retrieval strategies, chunking, evaluation, and performance tuning
  • Experience designing or contributing to agent-style AI systems and familiarity with agent evaluation, guardrails, and reliability testing
  • ML modeling experience beyond exploratory analysis such as supervised learning, ranking, classification
  • Understanding of software engineering best practices including testing strategies and CI/CD concepts
  • Experience working in Azure or similar cloud environments
  • Familiarity with Snowflake and optionally Snowflake AI as part of a modern data stack
  • Experience collaborating closely with domain experts
  • Financial domain exposure
  • Salary range for Hungary: 20100000 - 32400000 HUF
  • Annual discretionary bonus
  • Healthcare benefits
  • Leave benefits
  • Retirement benefits
  • Retirement investment and tools
  • Access to education reimbursement
  • Comprehensive resources to support physical health and emotional well-being
  • Family support programs
  • Flexible Time Off (FTO)
  • Hybrid work model with at least 4 days in office per week and 1 day remote work

Skills

See also

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