Applied AI/ML - Senior Associate

JPMorgan Chase & Co.•New York, NY

About The Position

As a Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate within our team, you will apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, and recommendation systems. You will collaborate with various teams and actively participate in the knowledge sharing community. You should excel in working in a highly collaborative environment together with the business, technologists, and control partners to deploy solutions into production. You should also have a strong passion for machine learning and invest independent time towards learning, researching, and experimenting with new innovations in the field. You must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn, and be highly motivated.

Requirements

BS with 5+ years, or MS with 3+ years of hand-on industry experience in Machine Learning - Deep Learning.
Good understanding of the latest advancement of NLP concepts, such as the transformer architecture and knowledge distillation.
Experience in classical ML techniques including classification, clustering, optimization, cross validation, data wrangling, feature selection, and feature extraction
Ability to design experiments — establish strong baselines, choose meaningful metrics, and evaluate model performance rigorously
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
Solid written and spoken communication skills

Nice To Haves

2 years of hands-on experience with virtual assistant model development and optimization
Familiarity with continuous integration models and unit test development
Experience with A/B experimentation and data/metric-promoten product development

Responsibilities

Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, or recommendation systems
Choosing, extending and innovating ML strategies for various banking problems
Analyzing and evaluating the ongoing performance of developed models
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
Learning about and understanding our supported businesses in order to promote practical and successful solutions