Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. In this role, you’ll apply strong technical judgment to choose the right approaches (including modern LLM-based methods where appropriate), evaluate performance with rigorous metrics, and ensure solutions are reliable, secure, and scalable in real-world environments. You’ll also contribute to improving data quality and feedback loops, monitoring models in production, and continuously iterating to reduce agent effort, shorten resolution times, and increase consistency and quality across operational workflows.
As an AI/ML Executive Director within Consumer & Community Banking (CCB) Recommendations & Personalization, you will lead the design and delivery of large-scale recommendation, ranking, and personalization systems that power customer experiences across CCB digital channels. You’ll drive strategy and execution across search/retrieval and NLP signals, experimentation, measurement, and production ML—leveraging GenAI where it meaningfully improves relevance, efficiency, or customer outcomes (but with recommenders and personalization as the core focus).
Job Responsibilities
- Own and evolve CCB recommendation & personalization platforms (candidate generation, ranking, re-ranking, retrieval, and real-time decisioning) to improve customer relevance and engagement across journeys and surfaces.
- Lead end-to-end ML delivery: problem framing, feature strategy, model development, offline/online evaluation, A/B testing, launch, monitoring, and iteration for production recommender systems.
- Develop and operationalize evaluation frameworks for ranking and personalization (e.g., relevance/utility metrics, calibration, novelty/diversity, long-term value, bias/fairness considerations, and guardrails).
- Apply NLP and search/retrieval techniques to enrich signals (query/document understanding, embeddings, semantic retrieval, entity/intent extraction) that improve recommendation quality and explainability.
- Use GenAI pragmatically to augment the recommendation stack (e.g., content understanding, synthetic labeling, summarization, conversational retrieval, or post-processing) with strong controls, evaluation, and risk awareness.
- Build and lead a high-performing team of applied scientists and ML engineers; set technical direction, raise engineering quality, and provide coaching and career development.
- Partner cross-functionally with Product, Design, Data, Risk/Controls, and Engineering to align on goals, prioritize roadmaps, and deliver measurable customer and business impact.
- Be a hands-on technical leader: contribute to architecture and critical code paths; guide system design for low-latency services, feature pipelines, training/inference infrastructure, and reliability.
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Promote a culture of rigor and learning by introducing modern recommendation methods, experimentation best practices, and strong documentation and knowledge sharing.
Required qualifications, capabilities, and skills:
- PhD in Computer Science (or equivalent experience) with strong research and industry background in machine learning, with depth in recommender systems, ranking, personalization, or information retrieval.
- Proven ability to lead and deliver large-scale production ML systems using big data, including recommenders (collaborative filtering, deep retrieval/ranking, sequence models), classification/regression, and causal/experimental methods.
- Strong track record of people leadership (building teams, setting technical direction, mentorship, performance management).
- Excellent written and verbal communication skills, including influencing senior stakeholders and translating business goals into measurable ML outcomes.
- 10+ years of hands-on programming and system-building experience (PhD + industry); strong in Python and at least one of Scala/Java; experience with Spark and distributed data processing.
- Solid fundamentals in data structures, algorithms, distributed systems, and databases, and experience building scalable, reliable ML services.
Preferred qualifications, capabilities, and skills:
- Deep expertise in ranking/retrieval/search (semantic retrieval, ANN/vector search, learning-to-rank), online experimentation, and real-time personalization.
- Experience designing feature stores, streaming/real-time pipelines, low-latency inference, and ML observability (data/model drift, performance diagnostics).
- Experience applying NLP/LLMs to improve recommendation systems (embeddings, query understanding, content signals, retrieval augmentation) with disciplined evaluation and governance.
- Familiarity with responsible AI considerations relevant to personalization (fairness, explainability, privacy, and control frameworks).
Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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.
Equal Opportunity Employer/Disability/Veterans
About the TeamOur Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.Skills Required
- PhD in Computer Science or equivalent experience with depth in recommender systems, ranking, personalization, or information retrieval
- Proven ability to lead and deliver large-scale production ML systems using big data (recommenders, ranking, retrieval, sequence models)
- Strong track record of people leadership, team building, mentorship, and performance management
- Excellent written and verbal communication skills; influence senior stakeholders and translate business goals into measurable ML outcomes
- 10+ years hands-on programming and system-building experience
- Strong in Python
- Proficiency in Scala or Java
- Experience with Spark and distributed data processing
- Solid fundamentals in data structures, algorithms, distributed systems, and databases; experience building scalable, reliable ML services
- Deep expertise in ranking/retrieval/search (semantic retrieval, ANN/vector search, learning-to-rank), online experimentation, and real-time personalization
- Experience designing feature stores, streaming/real-time pipelines, low-latency inference, and ML observability
- Experience applying NLP/LLMs to improve recommendation systems (embeddings, query understanding, retrieval augmentation) with governance
- Familiarity with responsible AI considerations (fairness, explainability, privacy, controls)
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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