About this role
Salary: £61,000 - 101,000 per year
Requirements: PhD in a quantitative field such as machine learning, AI, statistics, computer science, physics, or engineering, with 8 years of professional experience, or an MS in a quantitative field with 11 years of professional experience in machine learning, artificial intelligence, or related AI/data science and agent development work.Track record of leading complex, ambiguous technical initiatives end to end, from scoping through production, with measurable business impact.Experience managing or mentoring AI scientists or similar technical talent, including supporting career growth and development.Strong familiarity with Python programming and hands-on experience guiding solutions architecture for production-grade AI/ML systems.Strong theoretical background in and practical experience using AI, machine learning, optimization, or statistical techniques.Experience assessing machine learning and agentic system performance, including benchmark construction, metric design, and statistically sound measurement of quality, safety, and reliability.Depth in one or more research areas relevant to our work, such as LLM reasoning, reinforcement learning, machine learning, statistical modeling, or quantitative optimization.Academic publications, preprints, or open-source contributions.Experience building and deploying AI agents and agentic workflows using open-source frameworks, agent platforms, or comparable tools, including Model Context Protocol for connecting agents to tools and data.Experience with retrieval systems for agents, including retrieval-augmented generation, embedding models, vector databases, and long-term memory.Experience with machine learning libraries, cloud platforms, and the analysis of financial or economic data.Experience helping define technical standards, best practices, or ways of working adopted across multiple teams, and exposure to financial services or another regulated environment. Responsibilities: Own flagship AI Labs initiatives end to end, including scoping, stakeholder alignment, research, prototyping, build, and production deployment.Partner with senior business and technology stakeholders to turn ambiguous problems into scoped programs with agreed priorities and success criteria.Lead the design, build, and evaluation of AI agents and agentic workflows on large, complex datasets, iterating as findings emerge.Partner with engineering to make solutions production grade and compliant, with observability, guardrails, and evaluation pipelines in place.Manage and mentor AI scientists, guiding technical approach and career growth to build the bench in AI Labs.Communicate technical work and outcomes to senior leaders and general audiences, including white papers, publications, and presentations. Technologies: AIAI AgentsCloudEmbedding ModelsSupportLLMMachine LearningPythonAWSAzureGCPMCPPyTorchRESTTensorFlow More:
We are BlackRock AI Labs, our advanced AI science and engineering organization, partnering across the firm to solve complex challenges in financial services and deliver measurable business impact through generative AI, machine learning, optimization, and statistics. We are a hybrid team of scientists and engineers building production-scale solutions that help shape the future of BlackRock, with offices in New York, Edinburgh, Atlanta, San Francisco, and Seattle. We offer a wide range of employee benefits including retirement investment tools, education reimbursement, physical and emotional well-being resources, family support programs, and Flexible Time Off. We work in a hybrid model requiring at least 4 days per week in the office, with flexibility to work from home 1 day a week, and we are focused on collaboration, apprenticeship, performance, and innovation.
last updated 37 week of 2026