Machine Learning Scientist - Vice President

JPMorgan Chase; Plano (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

JPMorganChase is seeking an Applied AI Machine Learning Lead to drive scalable, production‑grade ML solutions across NLP, speech, recommendations, and information retrieval. You will lead multi‑step workflows with tool calling, agentic AI, and RAG, delivering privacy‑aware, productionized models that impact customer experiences.

You will design experiments, fine‑tune LLMs/SLMs, and collaborate with product, engineering, and governance teams to ensure robust deployments and measurable

Qualifications

• MS with 7+ years of hands-on industry experience in building and deploying ML systems (NLP/IR/RecSys/GenAI) in production.
• Strong understanding of transformer architectures, distillation, transfer learning, and representation learning.
• Applied GenAI experience with LLMs and fine-tuning of SLMs for targeted use cases, including prompt design and RAG.
• Experience with scaling LLM systems (caching, batching, governance, evaluation).

Responsibilities

• Lead and deploy state-of-the-art ML systems across NLP, speech, recommendations, and information retrieval.
• Design and build agentic AI systems for multi-step workflows with tool calling and multi-agent orchestration.
• Use RL and policy optimization to improve personalization and dialog policies.
• Fine-tune LLMs/SLMs using PEFT, distillation, and quantization while optimizing quality, latency, and cost.
• Collaborate with product, engineering, and control partners to deploy solutions.
• Analyze ongoing performance and ensure robust production operation.
• Build domain understanding to identify high-impact opportunities and ensure responsible AI usage.
• Implement privacy, safety, and security controls for GenAI systems.

Skills

NLP/IR/RecSys

GenAI/LLM

Python

Production ML

Experiment design

Cross-functional collaboration

Privacy & security

Education

MS in CS/ML

PhD in ML

Tools

PyTorch

TensorFlow

Hugging Face

scikit-learn

RAG tooling

Job description

Machine Learning Scientist - Vice President

Palo Alto, CA, United States

and 1 more

Job Information

• Job Identification 210706549

• Job Category Predictive Science

• Business Unit Consumer & Community Banking

• Posting Date 01/28/2026, 10:15 PM

• Locations 2100 El Camino Real, Palo Alto, CA, 94306, US8181 Communications Pkwy Bldg F, Plano, TX, 75024, US

• Job Schedule Full time

• Base Pay/Salary Palo Alto,CA $171,000.00-$260,000.00; Plano,TX $137,750.00-$235,000.00

Job Description

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.

As an Applied AI Machine Learning Lead, you will lead the development of scalable, production‑grade advanced ML solutions across natural language processing, speech recognition, recommendation systems, information retrieval, and agentic AI. You will play a key role in delivering Generative AI capabilities – designing and productionizing LLM‑powered systems such as RAG (Retrieval Augmented Generation), tool/function‑calling agents, and structured generation to automate complex workflows and improve customer experiences. You will collaborate with product, engineering, and control partners to translate ambiguous problems into measurable goals, deliver robust models, and operate them reliably in production. You bring strong deep learning and transformer‑based modeling expertise, as well as hands‑on experience in fine‑tuning and evaluation. You must have a strong passion for machine learning, strong analytical thinking, a deep desire to learn, and high motivation. You must also invest independent time in learning, researching, and experimenting with new innovations, and contribute to a strong knowledge‑sharing culture.

Job responsibilities

• Lead and deploy state‑of‑the‑art advanced machine learning systems across NLP, speech recognition, recommendation systems, and information retrieval.

• Design and build agentic AI systems for multi‑step workflows, including tool/function calling, multi‑agent orchestration, planning, grounding, and safety guardrails.

• Use reinforcement learning (policy optimization, bandits, RLHF‑style approaches where appropriate) to improve personalization, dialog policies, and sequential decision‑making systems.

• Fine‑tune and adapt LLMs/SLMs using PEFT (LoRA, AdaLoRA, IA3), distillation, and quantization; optimize for quality, latency, cost, and production constraints.

• Select and innovate on ML strategies for various banking problems.

• Analyze and evaluate the ongoing performance of developed ML systems.

• Collaborate with multiple partner teams, such as Business, Technology, Product Management, Design, Analytics, and Model Governance to deploy solutions into production.

• Build domain understanding to identify high‑impact opportunities, ensure responsible AI usage, and drive measurable outcomes (customer experience, automation, accuracy, and efficiency).

• Implement privacy, safety, and security controls for GenAI systems, including PCI handling/redaction, policy checks, jailbreak resistance, and auditability.

Required qualifications, capabilities, and skills

• MS with 7+ years, or PhD with 4+ years of hand‑on industry experience in building and deploying machine learning systems (NLP/Information Retrieval/Recommendation System and/or GenAI) in production environment

• Good understanding of the latest advancement of NLP concepts, such as the transformer architecture, knowledge distillation, transfer learning, and representation learning.

• Applied GenAI experience with LLMs and the ability to fine‑tune and deploy SLMs for targeted use cases, familiarity with prompt design, grounded generation, and RAG.

• Experience with scaling LLM systems (caching, batching, prompt/version governance, evaluation harnesses)

• Strong foundation in machine learning, deep learning, and statistical modelling, including model evaluation and error analysis.

• Solid understanding of Information Retrieval concepts (indexing, ranking, dense/sparse retrieval, re‑ranking) and/or recommendation systems.

• Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously

• Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments

• Proficiency in Python and common ML libraries (PyTorch/TensorFlow, Hugging Face, scikit‑learn), and ability to write production‑quality code.

• Ability to collaborate in cross‑functional environments with product, engineering, and control partners.

• Solid written and spoken communication skills

Preferred qualifications, capabilities, and skills

• 5 years of hands‑on experience with virtual assistant model development and optimization

• Experience orchestrating multi‑agent teams with supervisor agents, debate/consensus mechanisms, and role‑specialized toolkits for complex enterprise tasks.

• Building agent governance and eval suites: red‑teaming, adversarial tests, safety scorecards, regression suites for prompts/tools

• Experience with RL/bandits, preference optimization, or human feedback loops for personalization.

• Experience in regulated finance domains and working with risk/control processes.

• Experience with MLOps/LLMOps: CI/CD for models, monitoring/alerting, model versioning, evaluation of pipelines, and rollback strategies.

• Experience with A/B experimentation and data/metric‑driven product development.

About Us

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 (https://careers.jpmorgan.com/us/en/how-we-hire/faqs) for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About the Team

Our Consumer & Community Banking Group depends on innovators like you to serve consumers, small businesses, municipalities and non‑profits. You’ll support the delivery of award winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers.