The AI Labs was formed to act as a central hub with a firm-wide remit to solve strategic business challenges for the firm by bringing to bear our expertise in machine learning, artificial intelligence, data science and optimization. Our mission is to combine human and machine intelligence to revolutionize asset management. The team is led by Dr. Rachel Schutt, and co-head Professor Stephen Boyd, Samsung Professor of Engineering at Stanford.

We are a hybrid research and product team and have a responsibility to drive towards commercial impact in the form of alpha generation, operational efficiencies, and cost reduction. Building on the success of systematic investment teams with a history of demonstrating machine learning at BlackRock to create alpha, the goal was to apply these same techniques throughout the business.

The team has grown to 75+ data scientists and engineers. Working collaboratively, the team is multi-disciplinary with the following skills and capabilities: machine learning, optimization, statistical modeling, signal detection, natural language processing, data visualization, generative AI, network/graph modeling, ETL, data pipelines, data architecture, ML engineering, communication, product management and strategy. We work with data from a wide variety of sources including text, news feeds, financial reports, time series transactions, user behavior logs, and real-time data.

AI Labs has offices in New York, Palo Alto, Edinburgh, San Francisco, Atlanta and Gurgaon. The team has several Stanford professors as senior advisors with world-class expertise in machine learning, statistics, optimization and stochastic control. These advisors include Stephen Boyd, Emanuel Candes, Trevor Hastie, and Mykel Kochenderfer who dedicate time in our Palo Alto office and provide advice and guidance for the team.

We are looking for candidates with unique backgrounds and diverse skill sets with fresh perspectives to accelerate and amplify our efforts to make an impact at BlackRock. AI Labs aims to bring best of class technologies, analytics, and insights to the entirety of the firm and to our clients utilizing data from a wide variety of sources including text, news feeds, financial reports, time series transactions, logs, imagery, and real-time data.

In this role, you can expect to:

• Design and deliver secure and scalable solutions to enable the rapid delivery of machine learning products to production environments
• Continuously improve existing products, tools, and services, by maintaining close relationships with data scientists, researchers, and other BlackRock users
• Write quality maintainable code that is comprehensively tested and fit for the intended objective
• Provide ongoing maintenance and support for internal tools and services, including troubleshooting and resolution of production incidents
• Advise data scientists and researchers on product architecture and system design, and collaborate on complex deliverables
• Participate in team agile processes, and proactively contribute to team culture

The minimum requirements for this position are:

• Experience shipping code to production environments
• Strong programming language skills in Python and SQL
• Experience building cloud native applications
• Great problem-solving and communication skills

Knowledge and experience we are looking for includes:

• DevOps automation, idempotent deployment testing, and continuous delivery pipelines
• Networking and security protocols, load balancers, API Gateways
• ETL tooling and workflow engines (e.g., Spark, Airflow, Dagster, Flyte)
• Data modeling, and strategies for cleaning and validating data at scale
• Performance tuning on RDBMS or Big Data tools for row- and column-oriented use-cases
• Telemetry and related tools (metrics, event logging, tracing, etc.)
• Ability to traverse full stack

#EarlyCareers

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.

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.

For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock

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.