You will help shape how analytics and generative AI are delivered at enterprise scale—turning complex business problems into production-ready, measurable solutions. You will work with a collaborative team that values engineering excellence, responsible innovation, and continuous learning.
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 partner with stakeholders to shape problem statements, define success metrics, and deliver 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
- Develop generative AI, agent-based AI, and large language model solutions in Python from proof of concept through production deployment
- Design context engineering approaches to improve model accuracy, latency, reliability, and overall performance in real-world workflows
- Lead semantic modeling strategy, including ontology standards, governance, and lifecycle management aligned to enterprise needs
- Create scalable ontologies that model business entities, relationships, rules, and constraints in partnership with domain experts
- Define semantic integration patterns across data pipelines, application programming interfaces, data contracts, and experience layers to resolve semantic conflicts
- Build 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 methods
- Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and production operations
- Implement responsible AI practices, model risk controls, and governance aligned to regulated environments and internal standards
- Communicate complex technical concepts clearly to technical and non-technical stakeholders, including senior leaders, to align delivery to business objectives
Required qualifications, capabilities and skills
- Master’s degree in a data science-related discipline and 8 years of industry experience, or a PhD in a data science-related discipline
- Hands-on experience developing and deploying machine learning and generative AI solutions using Python
- Demonstrated ability to write and maintain production-quality code, including reliability, performance, and maintainability considerations
- Experience with continuous integration practices and unit test development to support quality delivery
- Experience building and managing data pipelines and processing workflows that support analytical and machine learning use cases
- Strong written and verbal communication skills, including the ability to translate technical decisions into business impact
- Demonstrated scientific thinking and structured problem-solving skills for ambiguous, data-driven challenges
- Ability to work independently while collaborating effectively across product, engineering, and business stakeholders
Preferred qualifications, capabilities and skills
- Experience building large language model applications that use context engineering to improve response quality and reliability
- Background in semantic modeling, ontology design, and governance practices in enterprise environments
- Experience designing semantic integration patterns across data contracts and application programming interfaces in distributed systems
- Experience implementing monitoring and evaluation approaches for machine learning and generative AI in production
- Experience mentoring data scientists and engineers and promoting modern machine learning engineering best practices
#LI-RB3
About UsWe 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
Skills Required
- Master's degree in a data science-related discipline and 8 years of industry experience, or a PhD in a data science-related discipline
- Hands-on experience developing and deploying machine learning and generative AI solutions using Python
- Demonstrated ability to write and maintain production-quality code, including reliability, performance, and maintainability considerations
- Experience with continuous integration practices and unit test development to support quality delivery
- Experience building and managing data pipelines and processing workflows that support analytical and machine learning use cases
- Strong written and verbal communication skills, including the ability to translate technical decisions into business impact
- Demonstrated scientific thinking and structured problem-solving skills for ambiguous, data-driven challenges
- Ability to work independently while collaborating effectively across product, engineering, and business stakeholders
- Experience building large language model applications that use context engineering to improve response quality and reliability
- Background in semantic modeling, ontology design, and governance practices in enterprise environments
- Experience designing semantic integration patterns across data contracts and application programming interfaces in distributed systems
- Experience implementing monitoring and evaluation approaches for machine learning and generative AI in production
- Experience mentoring data scientists and engineers and promoting modern machine learning engineering best practices
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.
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Healthcare Strength — Medical, dental, vision, and mental health coverage are comprehensive, with on-site clinics, preventive care, and specialized supports such as maternity nurse guidance and fertility treatments. Wellness activities can help offset copays and out-of-pocket costs, reinforcing the perceived strength of health benefits.
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Retirement Support — A 401(k) with dollar-for-dollar matching and additional automatic pay credits reflect strong employer-backed retirement savings. An employee stock purchase plan and related financial programs further bolster long-term financial support.
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Leave & Time Off Breadth — Paid time off, sick time, holidays, and generous parental leave are provided alongside family medical leave and adoption/fertility assistance. Additional programs like caregiver support and volunteer time off expand the breadth of time-away options.
JPMorganChase Insights
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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