Key responsibilities include:
- building and operating highly sophisticated end-to-end data and Machine Learning pipelines
- designing production APIs, data delivery processes
- integrating unstructured and timeseries data into production pipelines
- collaborating with DevOps engineers to plan and deploy data storage and processing systems, especially for text, timeseries or financial data
Requirements:
- Strong software Engineering experience
- Experience building and operating pipelines for processing and ML inference for text, timeseries or financial data
- Experience architecting, developing, and operating within AWS
- Proficiency in Python programming
- History of successfully collaborating with internal stakeholders and clarifying requirements
- Proven ability to iterate quickly
- (preferred) Experience working with Kubernetes, Airflow (or similar schedulers) and Machine Learning frameworks
- (preferred) Knowledge of Machine Learning algorithms such as common Deep Learning based Natural Language Processing (NLP) and Unsupervised Clustering
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
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. In accordance with applicable law, we make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as any mental health or physical disability needs.
