Senior Applied AI Researcher, Vice President

• Own AI projects or functional modules from

.

• Partner with

to translate real-world problems into clearly scoped data science and AI initiatives.

• Independently plan and execute research, experimentation, and iteration cycles in ambiguous problem spaces.

• Design AI solutions with a system‑level perspective, ensuring scalability, maintainability, and long‑term sustainability.

• Design and prototype

and agent-like workflows ( e.g. tool use, orchestration, multi-step reasoning).

• Contribute to defining system behavior, scope, and constraints, with attention to quality, robustness, and operational considerations.

• Stay current with emerging AI techniques and apply them pragmatically to solve business problems.

• Build and maintain

to assess AI system performance (accuracy, reliability, relevance, robustness, safety).

• Develop quantitative and qualitative metrics, benchmarks, and testing approaches to validate prototypes and track improvements.

• Analyze existing solutions to identify gaps and drive continuous, data-driven performance enhancements.

• Work closely with

to ensure smooth transition from prototype to production.

• Clearly communicate methods, assumptions, results, and limitations to

.

• Support engineering teams during implementation by clarifying evaluation criteria, edge cases, and expected system behavior.

• Serve as a technical authority and actively mentor junior data scientists, shaping best practices in experimentation, evaluation, and AI system design.

• Contribute actively within an

development environment.

• Apply good engineering hygiene in research and prototype code to enable reproducibility and collaboration.

, including probability, statistics, optimization, and model evaluation.

• Proven ability to select, apply, and critically evaluate ML models and algorithms for real-world problems.

• Strong

skills for analysis, modelling, experimentation, and prototyping.

• Strong

skills for data exploration, transformation, and analytical workflows.

• Excellent analytical thinking and problem-structuring abilities; comfort operating independently with loosely defined goals.

• Experience using

for version control and collaborative development.

• Strong

• Hands-on experience with

, including prompt/system design and building real-world applications.

• Experience with

, including retrieval strategies, chunking, evaluation, and performance tuning.

• Experience designing or contributing to

and familiarity with concepts such as agent evaluation, guardrails, and reliability testing.

• ML modeling experience ( e.g. supervised learning, ranking, classification) beyond exploratory analysis.

• Understanding of

, including testing strategies and CI/CD concepts.

• Experience working in

or similar cloud environments.

• Familiarity with

(and optionally Snowflake AI) as part of a modern data stack.

• Experience collaborating closely with domain experts;

• You independently deliver

and evaluation frameworks for a defined subdomain or application module.

• You proactively define scope, success metrics, and experimentation plans, helping shape architecture and design decisions.

• Your evaluation approaches enable reliable comparison, regression prevention, and continuous improvement of AI solutions.

• Engineering teams can confidently productionize your work thanks to clear designs, metrics, and collaboration.

• Over time, you raise the technical maturity of AI development and evaluation practices within the team.

The salary range for Hungary is 20100000 - 32400000 HUF Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.