Lead Machine Learning Engineer

J.P. Morgan; New York (NY); On-site; USD 150,000 - 230,000; Full time

Job summary

J.P. Morgan is seeking a Lead Machine Learning Engineer for the Digital Intelligence team in New York. You will build and maintain pipelines for distributed training, develop model promotion workflows, and optimize throughput on GPU clusters.

Collaboration across product and engineering teams will power Chase's digital channels with scalable ML platforms. The role combines deep ML expertise with software engineering, data science fundamentals, and observability to deliver reliable and secure

Qualifications

• BS in Computer Science or related Engineering with 6+ years, or MS with 4+ years.
• Strong Python and cloud computing knowledge with ML frameworks (PyTorch, TensorFlow).
• Deep knowledge of data science fundamentals, training and deploying models.
• Experience with monitoring/observability tools for model input/output and features.
• Experience with Ray, Spark, and training/inference systems like Ray, vllm/SGLang.
• Solid grounding in engineering fundamentals and enterprise system design.

Responsibilities

• Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters.
• Develop and manage pipelines for model promotion and MDLC capabilities.
• 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 ML Platform capabilities.
• Partner with product, architecture, modeling, and engineering to design robust solutions powering Digital channels.

Skills

Python

Cloud computing

PyTorch

TensorFlow

Monitoring tools

Ray

Spark

SGLang

Education

Bachelor's or MS in CS/Engineering

Tools

Docker

Kubernetes

Airflow

Kubeflow

Job description

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 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.

Come join us in reshaping the future!