Applied AI and Machine Learning Lead

JPMorganChase • Jersey City, NJ

7d

About The Position

As an Applied AI and Machine Learning Lead at JPMorganChase within the Data Science and AI team supporting the 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 scalable, robust, and responsibly deployed solutions. The role also includes setting semantic modeling standards and lifecycle governance, operationalizing production-grade machine learning and generative AI services, and mentoring engineers and data scientists.

Requirements

• 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, 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.
• Ability to partner across product, engineering, and business stakeholders to translate ambiguous needs into clear outcomes and delivery plans.

Nice To Haves

• 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.
• Hands-on 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 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.

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 evaluation practices covering quality, robustness, latency, cost, and risk, and translate results into recommendations and roadmaps.
• Build and operationalize production-grade machine learning and generative AI services using sound engineering practices, monitoring, and incident-ready controls.
• Lead semantic modeling standards and lifecycle governance in partnership with domain experts to drive consistency across systems.
• Implement integration patterns across 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 with business priorities and oversight expectations.
• Mentor and develop engineers and data scientists through technical leadership, reviews, and coaching.
• Communicate complex technical concepts to technical and non-technical audiences and influence decisions through clarity, evidence, and pragmatism.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior