Applied AI and Machine Learning Lead

Aumni; Jersey City (NJ); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorganChase, a leading global financial services firm, seeks an Applied AI and Machine Learning Lead within its Data Science and AI team to drive generative AI and analytics from research to production. You will design, evaluate, and deploy foundation-model and agentic AI capabilities to improve decision-making, automate work, and raise engineering standards.

You will partner with product, engineering, and risk stakeholders to define measurable outcomes, deliver scalable and governance-aligned

Qualifications

• 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 ML frameworks (e.g., 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 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.

Responsibilities

• 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.

Education

Master’s degree in computer science or related quantitative discipline

PhD in a quantitative field (preferred)

Tools

Git

GPU-enabled development workflows

Job description

As an Applied AI and Machine Learning Lead at JPMorganChase within the Data Science and AI team supporting our Technology organization, you will drive high-impact generative AI and advanced analytics initiatives from research through production. You will lead the design, evaluation, and deployment of foundation-model and agentic AI capabilities that improve decision-making, automate work, and raise engineering standards for reliability and governance. You will partner with product, engineering, and risk stakeholders to define measurable outcomes and deliver solutions that are scalable, robust, and responsibly deployed.

Job Responsibilities

• 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.

Required Qualifications, Capabilities, and Skills

• 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.

Preferred Qualifications, Capabilities, and Skills

• 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.

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

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. Lead foundation-model and agentic AI delivery to bring production-ready generative AI and trusted analytics to enterprise teams.