Machine Learning Operations Engineer, Senior Associate
New York, NY, United States
JPMorgan Chase & Co.
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.
As a Senior Machine Learning Operations Associate within our Consumer & Community Banking division, you will be responsible for building and maintaining pipelines for model training, 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
- Deploy and maintain infrastructure (eg., Sagemaker Notebooks) for providing an effective model development platform for data scientists and ML engineers that integrates with enterprise data ecosystem
- Build, deploy and maintain ingress/egress and feature generation pipelines to calculate input features for model training and inference
- Deploy and maintain infrastructure for batch and real-time model serving, in high throughput, low latency applications, at scale.
- Identify, deploy and maintain high quality model monitoring and observability tools
- Deploy and maintain infrastructure for compute intensive tasks such as hyperparameter tuning and interpretability and explainability
- Partners with product, architecture, and other engineering teams to define scalable and performant technical solutions.
- Leverages deep technical expertise to design extensible and scalable solutions, and to coach and grow individuals and teams.
- Ensures team executes work according to compliance standards, SLAs, and business requirements, to meet the objectives of an initiative. Anticipates the needs of broader teams and potential dependencies with other teams.
- Identifies and mitigates issues to execute a book of work while escalating issues as necessary.
- Proactively helps maintain high operational excellence standards for our production systems. Encourages development of technological methods and techniques
Required qualifications, capabilities, and skills
- BS degree in Computer Science or related Engineering field
- 3+ years applied experience
- Experience in model training, building, deployment and execution ecosystem such as Sagemaker and/or Vertex AI
- Experience in monitoring and observability tools to monitor model input/output and features stats
- Operational experience in data tools such as Spark, EMR, Ray
- Experience and interest in ML model architectures, linear or logistic regression, Gradient Boosted Trees, Neural Network architectures
- Experience in containers like docker ecosystem, container orchestration systems like Kubernetes, ECS and Airflow, Kubeflow etc.
- Experience with cloud technologies such as EC2, Sagemaker, IAM
Preferred qualifications, capabilities, and skills
- Bias for action and iterative development
- Experience with recommendation and personalization systems is a plus.
- Experience in programming languages such as Python and Java
- Familiarity of Databases
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 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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS Banking Computer Science Docker EC2 ECS Engineering Java Kubeflow Kubernetes Machine Learning ML models Model training Pipelines Python SageMaker Spark Testing Vertex AI
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