- Lead end-to-end generative AI and agentic AI initiatives from problem framing and experimentation through production release and measurable adoption.
- Design and evaluate foundation-model approaches, including model selection, fine-tuning strategies, retrieval and context design, and safety controls.
- Establish rigorous evaluation practices (quality, robustness, latency, cost, and risk) and translate results into clear recommendations and roadmaps.
- Build and operationalize production-grade machine learning and generative AI services using sound engineering practices, monitoring, and incident-ready controls.
- Define and drive semantic consistency across systems by leading semantic modeling standards and lifecycle governance in partnership with domain experts.
- Implement integration patterns that align data pipelines, application interfaces, and user experiences to reduce semantic conflicts and increase trust in outcomes.
- Partner with cross-functional leaders to define success metrics, manage trade-offs, and deliver outcomes aligned to business priorities and oversight expectations.
- Mentor and develop engineers and data scientists through technical leadership, reviews, and coaching to raise team capability and delivery velocity.
- Communicate complex technical concepts to both technical and non-technical audiences, influencing decisions through clarity, evidence, and pragmatism.
- Master’s degree in computer science, engineering, statistics, or a related quantitative discipline.
- 7+ years of applied experience building and deploying machine learning and generative AI solutions in production environments.
- Strong proficiency in Python and modern machine learning frameworks (for example, PyTorch).
- Demonstrated ability to lead experimentation and evaluation, including defining metrics, running controlled comparisons, and documenting results for stakeholders.
- Experience deploying and operating models in production, including performance optimization, monitoring, and reliability trade-offs.
- Working knowledge of responsible AI practices, model risk concepts, and governance controls suitable for regulated environments.
- Strong software engineering fundamentals, including version control, code review, testing, and maintainable design.
- Proven ability to partner across product, engineering, and business stakeholders to translate ambiguous needs into clear outcomes and delivery plans.
- PhD in a relevant quantitative field or demonstrated applied research impact in machine learning or generative AI.
- Publications, patents, or open-source contributions that demonstrate research depth and practical impact.
- Hands-on experience with transformer-based architectures, large-scale training or fine-tuning, and GPU-enabled development workflows.
- Experience building agentic AI systems (tool use, orchestration, planning, and workflow automation) with strong evaluation discipline.
- Familiarity with semantic modeling, ontologies, or semantic-layer design to improve consistency across analytics and AI use cases.
- Experience applying AI solutions within financial services or other highly regulated industries.
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
Skills Required
- Master's degree in computer science, engineering, statistics, or a related quantitative discipline
- 7+ years of applied experience building and deploying machine learning and generative AI solutions in production environments
- Strong proficiency in Python and modern machine learning frameworks such as PyTorch
- Experience leading experimentation and evaluation, including defining metrics, controlled comparisons, and stakeholder documentation
- Experience deploying and operating production models, including performance optimization, monitoring, and reliability trade-offs
- Knowledge of responsible AI practices, model risk concepts, and governance controls for regulated environments
- Strong software engineering fundamentals, including version control, code review, testing, and maintainable design
- Ability to partner across product, engineering, and business stakeholders to translate ambiguous needs into outcomes and delivery plans
- PhD in a relevant quantitative field or demonstrated applied research impact in machine learning or generative AI
- Publications, patents, or open-source contributions demonstrating research depth and practical impact
- Experience with transformer-based architectures, large-scale training or fine-tuning, and GPU-enabled development workflows
- Experience building agentic AI systems involving tool use, orchestration, planning, and workflow automation
- Familiarity with semantic modeling, ontologies, or semantic-layer design
- Experience applying AI solutions in financial services or other highly regulated industries
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 — Health coverage is considered comprehensive, including medical, dental, and vision, alongside wellness and mental health resources. Some locations add onsite health centers and related wellbeing support.
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Retirement Support — Retirement offerings include a 401(k)-type savings plan and related financial benefits, with options such as employee stock purchase participation. Financial planning resources are also highlighted to support long-term savings.
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Parental & Family Support — Paid parental leave of 16 weeks for birth or adoption is available for all parents. Child care and back-up child care resources further reinforce family support.
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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