Applied Artificial Intelligence and Machine Learning Lead

JPMorgan Chase & Co.
United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Computer Programming Python (Programming Language) Machine Learning Reliability Engineering Tensorflow Software Engineering Pytorch Kubernetes Low Latency Free and Open-Source Software
+1 more
Machine Learning Operations

Job description

Join JPMorganChase, where you can help shape how applied artificial intelligence and machine learning accelerate decision-making, improve efficiency, and unlock new client value. You will partner with product, engineering, and business leaders to build reusable agent platform capabilities that are reliable, scalable, and responsible.

As an Applied Artificial Intelligence and Machine Learning Lead at JPMorganChase within our agent platform team, you will drive the delivery of production-ready agent capabilities and developer tooling that enable teams to safely build and operate agent-based solutions. You will set technical direction, raise engineering standards, and influence architecture decisions that balance speed, risk, and long-term maintainability. You will also mentor engineers and practitioners while collaborating across teams to align platform outcomes to measurable business impact., * Define and drive the platform roadmap for agent-based capabilities, focusing on measurable outcomes, reliability, and usability

  • Lead end-to-end delivery of core agent platform components, including software development kits, reference implementations, and integration patterns
  • Partner with product, engineering, risk, and control stakeholders to align requirements, prioritize trade-offs, and unblock execution
  • Establish quality, performance, and operational standards for agent workloads, including monitoring, testing, and incident readiness
  • Translate experimentation into production by driving clear architecture decisions, scalable designs, and repeatable deployment practices
  • Guide responsible development practices by embedding governance, privacy, and model risk considerations into platform design
  • Mentor and develop team members through technical coaching, design reviews, and continuous improvement of engineering practices
  • Communicate technical strategy and progress to senior stakeholders with clarity, data, and pragmatic recommendations, Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Requirements

  • Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience
  • Demonstrated experience building and operating production software systems that integrate machine learning capabilities
  • Strong programming skills in at least one modern language (for example, Python, Java, or Go) and experience with modern software engineering practices
  • Hands-on experience with machine learning frameworks (for example, PyTorch, TensorFlow, or JAX) and model lifecycle tooling
  • Experience designing platforms or shared services used by multiple teams, including clear interfaces, documentation, and developer experience focus
  • Working knowledge of cloud and container orchestration concepts (for example, Kubernetes) and performance or reliability engineering fundamentals
  • Proven ability to lead through influence, drive technical alignment, and deliver outcomes across cross-functional partners
  • Strong problem-solving skills, including ability to clarify ambiguity, evaluate trade-offs, and make sound technical decisions

Preferred qualifications, capabilities and skills

  • Experience building agent-based systems, orchestration patterns, or agent development tooling and evaluation frameworks
  • Experience designing scalable inference or model serving architectures, including latency, throughput, and cost optimization
  • Familiarity with responsible artificial intelligence practices, model risk concepts, and governance-by-design approaches
  • Experience contributing to or maintaining widely used open-source software in machine learning or infrastructure ecosystems
  • Domain knowledge applying machine learning to regulated financial services use cases

About the company

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

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