Lead Machine Learning Engineer

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 Lead Machine Learning Engineer on the Digital Intelligence team, you will be

collaborating with a high-caliber team of software developers and deep learning

experts, you’ll build and maintain pipelines for distributed model training on

large compute clusters, hyperparameter tuning at scale, model monitoring, design

and develop ML frameworks and components used for various model implementations.

Job responsibilities

* Build, deploy, and maintain robust pipelines for distributed training on

GPU-enabled clusters to support scalable machine learning workflows.

* Develop and manage pipelines for model promotion and other capabilities

related to MDLC.

* Optimize training throughput for large data sources

* Establish and maintain integrations to platforms and tools related to model

monitoring and observability

* Collaborate with cross-functional teams to integrate new technologies and

improve the capabilities of our ML Platform.

* Partner with product, architecture, modeling, and engineering to design

robust solutions that power our Digital channels

Required qualifications, capabilities, and skills

* BS in Computer Science or related Engineering field with 6+ years of

experience Or MS degree in Computer Science or related Engineering field with

4+ years experience.

* Solid knowledge and extensive experience in Python and in cloud computing,

along with ML frameworks (i.e. pytorch, tensorflow)

* Deep knowledge and passion for data science fundamentals, training and

deploying models

* Experience in monitoring and observability tools to monitor model

input/output and features stats

* Operational experience in big data/ML tools such as Ray, Spark and in

training/inference systems such as Ray, vllm/SGLang

* Solid grounding in engineering fundamentals and enterprise system design

Preferred qualifications, capabilities, and skills

* Experience with recommendation and personalization systems is a plus.

* CUDA experience is a big plus

* Solid fundamentals and experience in containers (docker ecosystem), container

orchestration systems [Kubernetes, ECS], DAG orchestration [Airflow, Kubeflow

etc]

* Good knowledge of data storage solutions and strategies (online and offline)

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

[https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about

requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

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.

The CCB Data & Analytics team responsibly leverages data across Chase to build

competitive advantages for the businesses while providing value and protection

for customers. The team encompasses a variety of disciplines from data

governance and strategy to reporting, data science and machine learning. We have

a strong partnership with Technology, which provides cutting edge data and

analytics infrastructure. The team powers Chase with insights to create the best

customer and business outcomes.