Lead Machine Learning Engineer-MLOps

We are looking for a Senior MLOps engineer to work closely with Data Scientists

to build and deploy ML models on a modern MLOps stack.

As Lead Machine Learning Engineer on the Recommendation Engine team, you’ll

build and maintain pipelines for distributed model training on large compute

clusters, batch/real-time model serving, hyperparameter tuning at scale, model

monitoring, production validation and other activities vital for model

development, testing and deployment in a well-managed, controlled environment.

Our product, Personalization and Insights, builds and supports high throughput,

low latency applications which leverage state of the art machine learning

architectures, and which are deployed in AWS. These applications power

personalized experiences across Chase Consumer & Community Banking channels, to

help weave a user experience that includes traditional banking services with

other services in the Travel, Merchant Offer Shopping, and Dining spaces.

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 high-throughput, real-time inference as well

as batch inference, ensuring optimal performance and reliability.

* Implement quantization techniques and deploy large language models (LLMs) to

maximize efficiency and resource utilization.

* Oversee the management and optimization of vector databases to support

advanced AI and machine learning applications.

* Establish and maintain comprehensive monitoring and observability pipelines

to ensure system health, performance, and rapid issue resolution.

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

continuously improve existing infrastructure.

* Partner with product, architecture, and other engineering teams to define

scalable and performant technical solutions.

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,

preferably AWS

* Understanding of quantization techniques such as PTQ, AWQ etc. used to

quantize LLMs for accelerating inference on specific GPU architectures

* Experience in systems engineering fundamentals: caching, CUDA, autoscaling,

high throughput, low latency, x-region resilient applications

* 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, DuckDB, Spark and in

training/inference systems such as Ray, vllm/SGLang

* Solid grounding in engineering fundamentals and analytical mindset

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 Databases

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

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking,

markets, securities services and payments. Corporations, governments and

institutions throughout the world entrust us with their business in more than

100 countries. The Commercial & Investment Bank provides strategic advice,

raises capital, manages risk and extends liquidity in markets around the world.