Job description

About this role AI Labs Overview For more than three decades, BlackRock has combined world-class talent and technology to redefine what s possible in asset management. Today, AI is reshaping every aspect of our industry, from investments and client experiences to operations, risk management, and product innovation. BlackRock AI Labs sits at the center of that transformation. AI Labs is BlackRock s advanced AI science and engineering organization. We partner with teams across the firm to solve some of the most complex and consequential challenges in financial services, applying generative AI, machine learning, optimization, and statistics to deliver measurable business impact. Our mission is simple but ambitious: combine human and machine intelligence to revolutionize asset management. What sets AI Labs apart is our ability to move from idea to impact. We are not a research lab detached from the business, nor are we a traditional software engineering organization. We are a hybrid team of scientists and engineers who build solutions that run at scale in production environments and create capacity for our business partners. From AI-powered investment insights and risk management solutions to next-generation agentic workflows and enterprise AI platforms, our work is helping to shape the future of BlackRock. Our teams work on some of the firm s highest priority strategic initiatives, including large-scale generative AI systems, intelligent agents, predictive analytics, optimization engines, operational risk solutions, and AI platforms that accelerate innovation across BlackRock. We help define best practices, establish technical standards, and enable teams throughout the organization to adopt AI safely, effectively, and at scale. AI Labs has offices in New York, Edinburgh, Atlanta, San Francisco and Seattle. 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. In this role, you can expect to: Provide technical leadership, set architectural direction, and drive key design decisions across multidisciplinary teams. Design, build, and operate production AI/ML systems across areas such as generative AI, intelligent agents, predictive modeling, and optimization. Develop reusable AI platforms, services, and infrastructure that accelerate experimentation, deployment, monitoring, and adoption across the firm. Translate emerging AI capabilities into robust, scalable solutions that deliver measurable business impact. Define evaluation, testing, and observability approaches for AI systems, including non-deterministic and agentic applications. Optimize AI systems and workloads for latency, throughput, compute efficiency, reliability, security, and cost. Partner with business, engineering, data, risk, and control teams to take solutions from concept through production deployment and ongoing operation. Establish engineering standards, mentor engineers, and influence technical strategy across teams. The minimum requirements for this position are: 12 years of software engineering experience, including significant experience designing, building, and operating complex production systems. 6 years of experience building and deploying AI/ML, optimization, or other model-driven applications in production. Strong proficiency in Python and a track record of developing maintainable, well-tested production software. Strong SQL skills and experience working with data-intensive applications and large-scale datasets. Experience designing and building APIs, services, data pipelines, or distributed systems that support AI/ML applications. Experience with containerization and orchestration technologies, such as Docker and Kubernetes. Demonstrated ability to lead complex technical solutions from architecture and design through production deployment, operation, and continuous improvement. Strong problem-solving, collaboration, and communication skills, with the ability to influence technical decisions across multidisciplinary teams. Additional knowledge and experience we value includes: Experience collaborating with research teams in fast-moving environments, ideating quickly on research prototypes. Generative AI, large language models, AI agents, and architectures for production AI systems. Evaluation, experimentation, observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications. Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX. Distributed systems, cloud infrastructure, model serving, orchestration, data pipelines, and API design. Performance optimization across latency, throughput, compute utilization, reliability, scalability, and cost. Responsible AI, security, governance, and controls in enterprise or regulated environments. Experience with a systems- or performance-oriented programming language such as Rust, C , C, Go, or Zig. Experience in financial services or another regulated industry. Relevant Knowledge, Skills, and Abilities: • Machine learning frameworks (TensorFlow, PyTorch, scikit-learn) • Programming languages (Python, R, Java) • Deep learning, NLP, computer vision techniques • Cloud ML platforms (AWS SageMaker, Azure ML, Vertex AI) • MLOps tools and practices • Statistical analysis and experimentation For Atlanta, GA Only the salary range for this position is USD$170,000.00 - USD$220,000.00 . 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 benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents 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 workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement . BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance blackrock.com . All requests are treated in line with our privacy policy . BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.

Requirements

Must-haves

AI Labs Overview
AI Labs has offices in New York, Edinburgh, Atlanta, San Francisco and Seattle.
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.
Provide technical leadership, set architectural direction, and drive key design decisions across multidisciplinary teams.
Design, build, and operate production AI/ML systems across areas such as generative AI, intelligent agents, predictive modeling, and optimization.
Develop reusable AI platforms, services, and infrastructure that accelerate experimentation, deployment, monitoring, and adoption across the firm.
Translate emerging AI capabilities into robust, scalable solutions that deliver measurable business impact.
Define evaluation, testing, and observability approaches for AI systems, including non-deterministic and agentic applications.
Optimize AI systems and workloads for latency, throughput, compute efficiency, reliability, security, and cost.
Partner with business, engineering, data, risk, and control teams to take solutions from concept through production deployment and ongoing operation.
Establish engineering standards, mentor engineers, and influence technical strategy across teams.
12 years of software engineering experience, including significant experience designing, building, and operating complex production systems.
6 years of experience building and deploying AI/ML, optimization, or other model-driven applications in production.
Strong proficiency in Python and a track record of developing maintainable, well-tested production software.
Strong SQL skills and experience working with data-intensive applications and large-scale datasets.
Experience designing and building APIs, services, data pipelines, or distributed systems that support AI/ML applications.
Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
Demonstrated ability to lead complex technical solutions from architecture and design through production deployment, operation, and continuous improvement.
Strong problem-solving, collaboration, and communication skills, with the ability to influence technical decisions across multidisciplinary teams.
Additional knowledge and experience we value includes:
Experience collaborating with research teams in fast-moving environments, ideating quickly on research prototypes.
Generative AI, large language models, AI agents, and architectures for production AI systems.
Evaluation, experimentation, observability, debugging, and testing approaches for AI/ML systems, including non-deterministic and agentic applications.
Machine learning and optimization frameworks such as PyTorch, TensorFlow, or JAX.

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Keywords to mirror

aimachine learningmlpythonsqldockerkubernetesapirustgojavaawsazure

Platform: workday
Effort: long

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