Machine Learning Engineer

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Job Description

Why American Express?

 
There’s a difference between having a job and making a difference.
 
American Express has been making a difference in people’s lives for over 160 years, backing them in moments big and small, granting access, tools, and resources to take on their biggest challenges and reap the greatest rewards.
 
We’ve also made a difference in the lives of our people, providing a culture of learning and collaboration, and helping them with what they need to succeed and thrive. We have their backs as they grow their skills, conquer new challenges, or even take time to spend with their family or community. And when they’re ready to take on a new career path, we’re right there with them, giving them the guidance and momentum into the best future they envision.
 
Because we believe that the best way to back our customers is to back our people.
 
The powerful backing of American Express.
Don’t make a difference without it.
Don’t live life without it.

 

If you have a strong will to learn and educate and are motivated by the opportunity to help grow our team and be a part of an industry-leading technology and innovation organization, then look no further! This is an opportunity to combine Data Science and Engineering skills to solve very interesting problems that directly and greatly impact millions of individuals worldwide. There are hundreds of opportunities to make your mark on technology and life at American Express.

 

American Express is embarking on an exciting transformation on building the next generation customer first ecosystem for democratizing Machine Learning in Amex on the Cloud. You will be part of an energetic Data Science/Machine Learning team, to drive strategic planning and a cohesive set of technology and machine learning solutions enabling data and platform transformation, by collaborating across all channel teams and the critical technology platforms that support Colleague and Customer Experiences. This position provides an opportunity to solve very interesting problems that directly and greatly impact millions of individuals worldwide. If you have the talent and desire to deliver innovative and intelligent products as well as services at a rapid pace, serving our colleagues and customers seamlessly across through cognitive solutions, this would be the right fit for you!

 

Responsibilities:

  • More than 70%+ of the time spent on coding and/or hands-on technical implementation of re-usable frameworks to drive adoption of Machine Learning in Amex
  • Combine Data Science and Engineering skills to solve very interesting problems that directly and greatly impact millions of individuals worldwide
  • Not only creating ML model prototypes, but also putting them into production in scale
  • Challenge the way we do business through application of technology and machine learning solutions to integrate insights in the operational workflow 
  • Be part of a dynamic team and play a visible role in implementing cutting-edge technology and machine learning solutions with other industry-leading partners
  • Works with large, complex data sets to build products and tools that enhance colleague and customer experiences
  • Implement highly scalable platform components and tools leveraging machine learning and deep learning models to solve real-world problems in areas such as Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions
  • You will be part of a Data Science / Machine Learning team to design, code, train, test, deploy and iterate on large scale machine learning systems
  • You will work with Engineering, Analytics, and Data Science experts to strive for greater functionality in technology ecosystem
  • You will help craft the direction of machine learning and artificial intelligence at AmEx

Qualifications

  • Master or PhD degree in Computer Science, Computer Engineering, EE, EEE, Statistics, Math, Industrial Engineering, Operational Research, Physics, or related fields.
  • Strong analytical skills and programming skills, in production environment.
  • 2+ years hands-on experience with the following technologies:
    • SQL/ NoSQL
    • Python, and/or Java
    • Big Data
    • Once of the popular Machine Learning technologies such as TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon etc.
    • RESTAPI and services
  • 2+ years of experience in specialized areas such as Machine Learning, Deep Learning, Reinforcement Learning, NLP, Optimization, Probabilistic Inference, Information Retrieval, Recommendation Systems
  • Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
  • Experience supporting and working with cross-functional teams in a dynamic environment

Preferred Qualifications:

  • Deep expertise in building scalable Machine Learning powered applications
  • 3+ years hands-on experience with the following technologies:
    • SQL/ NoSQL
    • Python, and/or Java
    • Big Data
    • One of the popular Machine Learning technologies such as TensorFlow, Keras, ScikitLearn, H20.ai, MXNet, Caffe, Gluon, RESTAPI and services, etc.
  • Expert in specialized areas such as Machine Learning, Deep Learning, Reinforcement Learning, NLP, Optimization, Probabilistic Inference, Information Retrieval, Recommendation Systems.
  • Direct involvement in working with large volumes of data and building, deploying and measuring in production environment
  • Experience with data pipeline and workflow management tools: Apache NiFi, Informatica, Talend, DataStage, Alteryx, etc. is a plus
  • Hands-on experience with GCP, AWS, Hadoop Ecosystem, Spark is a plus.
  • Hands-on experience with relational SQL and NoSQL databases: Redshift, Snowflake, DynamoDB, Neo4J, MongoDB, Cassandra, DataStaX, etc. is a plus
  • Knowledge of / experience with multi/cross/omni-channel CX is a plus

Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions. 



ReqID: 19019088
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Oct 22, 2019, 2:12:23 PM