Senior Applied AI Researcher, Vice President

Own AI projects or functional modules fromproblem definition through prototype validation and production support.

Partner withproduct managers and business stakeholdersto 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.

Applied AI, LLMs, and agentic systems

Design and prototypeLLM-powered solutions, includingRAG-based systemsand 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.

Evaluation, validation, and performance improvement

Build andmaintainevaluation frameworksto assess AI system performance (accuracy, reliability, relevance, robustness, safety).

Develop quantitative and qualitative metrics, benchmarks, and testing approaches tovalidateprototypes and track improvements.

Analyze existing solutions toidentifygaps and drive continuous, data-driven performance enhancements.

Collaboration and communication

Work closely withdata scientists, engineers, and product teamsto ensure smooth transition from prototype to production.

Clearly communicate methods, assumptions, results, and limitations totechnical and non-technical audiences.

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.

Ways of working

Contribute actively within anAgile / SCRUMdevelopment environment.

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

Required Qualifications

6+ yearsof 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.

StrongPythonskills for analysis, modelling, experimentation, and prototyping.

StrongSQLskills for data exploration, transformation, and analytical workflows.

Excellent analytical thinking and problem-structuring abilities; comfortoperatingindependently with loosely defined goals.

Experience usingGitfor version control and collaborative development.

StrongEnglish communication skills, both written and verbal.

Preferred Qualifications (Strong Plus)

Hands-on experience withLLMs, including prompt/system design and building real-world applications.

Experience withRAG systems, including retrieval strategies, chunking, evaluation, and performance tuning.

Experience designing or contributing toagent-style AI systemsand familiarity with concepts such as agent evaluation, guardrails, and reliability testing.

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

Understanding ofsoftware engineering best practices, including testing strategies and CI/CD concepts.

Experience working inAzureor similar cloud environments.

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

Experience collaborating closely with domain experts;financial domain exposure is a plus but notrequiredfor strong technical candidates.

What Success Looks Like in This Role

You independently deliverhigh-quality AI prototypesand 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 confidentlyproductionizeyour 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.

Our benefits

To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.

Our hybrid work model

BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.

Guidance on AI use for candidates

At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.

To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.