Applied AI and ML Lead - Generative AI

Posted 4 Hours Ago
Be an Early Applicant
2 Locations
Hybrid
Senior level
Financial Services
We’re one of the world’s biggest technology-driven companies
The Role
Lead design, build, and deploy scalable generative AI and ML solutions from prototype to production. Define semantic modeling and ontology strategy, integrate semantics across data pipelines and APIs, enable ontology-driven agents and workflows, implement MLOps, monitoring, and responsible AI controls, and mentor engineers and data scientists to deliver measurable business outcomes.
Summary Generated by Built In

Build what’s next in enterprise AI—solutions that materially improve how teams make decisions, automate work, and serve internal customers. You will take generative AI from concept to production, help set the standard for semantic consistency across systems, and partner closely with stakeholders to turn complex business needs into measurable outcomes. You will mentor talent and influence technical direction across Corporate Technology and supported Corporate Functions.

As an Applied AI and Machine Learning Lead at JPMorganChase within Corporate Technology Data Science and AI, you will design, build, and deploy scalable analytical and generative AI solutions that deliver measurable business value. You will translate complex business needs into clear problem statements, success metrics, and production-ready models and intelligent workflows. You will help establish semantic modeling standards and a unified semantic layer that improves trust and consistency across analytics and AI use cases.


Job Responsibilities

  • Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment with measurable outcomes
  • Design context engineering approaches to improve model accuracy, latency, reliability, and end-to-end user experience
  • Lead enterprise semantic modeling strategy, including ontology standards, governance practices, and lifecycle management
  • Partner with domain experts to create scalable ontologies that represent business entities, relationships, rules, and constraints
  • Define semantic integration patterns across data pipelines, application programming interfaces (APIs), data contracts, and experience layers to resolve semantic conflicts
  • Establish and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
  • Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration approaches
  • Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations
  • Implement responsible AI practices, model risk controls, and governance aligned to regulated environments
  • Mentor engineers and data scientists, raising the bar on engineering rigor, reuse, and continuous improvement across the team

Required Qualifications, Capabilities, and Skills

  • Master’s degree in a data science-related discipline and eight years of industry experience, or PhD in a data science-related discipline
  • Demonstrated experience developing and deploying machine learning and generative AI solutions using Python
  • Proven ability to write and maintain production-quality code, including documentation and maintainable design patterns
  • Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines
  • Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases
  • Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition
  • Strong written and verbal communication skills, with the ability to explain complex concepts to technical and non-technical stakeholders
  • Demonstrated ownership and attention to detail when operating in ambiguous, complex problem spaces
  • Ability to work independently while collaborating effectively across product, engineering, data, and business partners

Preferred Qualifications, Capabilities, and Skills

  • Experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance
  • Experience implementing retrieval-augmented generation, tool use, and evaluation strategies for large language model applications
  • Familiarity with responsible AI techniques, including bias testing, explainability approaches, and model monitoring standards
  • Experience designing scalable architectures for real-time or near-real-time inference and intelligent workflow orchestration
  • Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution

#LI-RB3

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About the TeamOur Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You’ll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.

Skills Required

  • Master's degree in a data science-related discipline and eight years of industry experience, or PhD in a data science-related discipline
  • Experience developing and deploying machine learning and generative AI solutions using Python
  • Proven ability to write and maintain production-quality code, including documentation and maintainable design patterns
  • Experience building automated testing practices, including unit tests, and implementing continuous integration pipelines
  • Experience building and managing data pipelines and processing workflows for analytics and machine learning use cases
  • Strong scientific thinking and structured problem-solving skills, including hypothesis-driven analysis and metric definition
  • Strong written and verbal communication skills, with ability to explain complex concepts to technical and non-technical stakeholders
  • Demonstrated ownership and attention to detail when operating in ambiguous, complex problem spaces
  • Ability to work independently while collaborating effectively across product, engineering, data, and business partners
  • Experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance
  • Experience implementing retrieval-augmented generation, tool use, and evaluation strategies for large language model applications
  • Familiarity with responsible AI techniques, including bias testing, explainability approaches, and model monitoring standards
  • Experience designing scalable architectures for real-time or near-real-time inference and intelligent workflow orchestration
  • Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution

JPMorganChase Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.

  • Healthcare Strength Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
  • Parental & Family Support Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
  • Retirement Support Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.

JPMorganChase Insights

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The Company
HQ: New York, NY
289,097 Employees
Year Founded: 1799

What We Do

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.

Why Work With Us

Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.

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