As an Applied AI ML Lead within the Digital Intelligence team at JPMorgan, you will have the opportunity to collaborate with all lines of business and functions to deliver software solutions. You will experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a significant impact on technology and business. You will also design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to promote and optimize business results. This role provides an exciting opportunity to contribute to a transformative journey and make a substantial impact on a wide range of customer products.
Job Responsibilities:
- As a Machine Learning Engineer in the banking domain, you will be responsible for designing and implementing end to end machine learning solutions for production environment to solve complex problems related to personalized financial services in retail and digital banking domain. You will work closely with other fellow Machine Learning practitioners and cross-functional teams to translate business requirements into technical solutions and drive innovation in our banking products and services.
- You will collaborate with Machine Learning engineers, product managers, key business stakeholders, engineering and platform partners to deploy projects that delivers cutting edge machine learning driven digital solutions.
- You will write codes to create several machine learning experimentation pipelines.
- You will design and implement feature engineering pipelines and push them to feature stores. You will collaborate with data engineers and product analysts to preprocess and analyze large datasets from multiple sources.
- You will execute experiments and validations at scale, review results with Lead and Products.
- You will be responsible to create model serving pipelines that meets consumption SLAs.
- You will be responsible for writing production grade code for both training and inference functions.
- You will collaborate with MLOps engineers in developing and testing the training and inference applications under production architecture blueprint often in integration with upstream and downstream applications.
- You will collaborate with MLOps engineers to register the models artifacts, maintain code repos, prepare for CI/CD execution and post production monitoring set ups.
- You will be responsible to drive end to end system architecture in collaboration with ML, MLOps and Architecture leads.
- You will communicate and collaborate with Platform and Engineering partners to bring in the latest advancements in order to improve the scale, consistency, reliability and trustworthiness of the ML solutions
Required qualifications, capabilities and skills:
- BS, MS or PhD degree in Computer Science, Statistics, Mathematics or Machine learning related field.
- Expert proficiency in implementing ML models at least one of the following areas: Natural Language Processing, Knowledge Graph, Computer Vision, Speech Recognition, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis.
- Foundational knowledge in Data structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, Statistics.
- Demonstrated expertise in machine learning frameworks: Tensorflow, Pytorch, pyG, Keras, MXNet, Scikit-Learn.
- Expert programming knowledge of python, spark; Expert coding knowledge on vector operations using numpy, scipy;
- Coding knowledge on distributed computation using Multithreading, Multi GPUs, Dask, Ray, Polars etc.
- Strong analytical and critical thinking skills for problem solving.
- Excellent written and oral communication along with demonstrated teamwork skills.
- Demonstrated ability to clearly communicate complex technical concepts to both technical and non-technical audiences.
- Experience in working with interdisciplinary teams and collaborating with other researchers, engineers, and stakeholders.
Preferred qualifications, capabilities and skills:
- Experience with distributed data/feature engineering using popular cloud services like AWS EMR
- Experience with large scale training, validation and testing experiments
- Experience with cloud Machine Learning services in AWS i.e. Sagemaker
- Experience with Container technology like Docker, ECS etc.
- Experience with Kubernetes based platform for Training or Inferencing
JPMorgan Chase & Co., 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 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.
