American Express Careers
AI Machine Learning Engineer
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.
- 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 the Enterprise
- Leading your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.
- Architecting, estimating and planning technical solutions to problems
- Implement new, 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 and Time Series predictions
- Actively participate in team and company-wide architecture and engineering discussions and forums
- At least 5+ years of progressive experience with a broad set of tech stacks, hands-on Machine Learning and Big Data is mandatory as part of the job
- Deep expertise in building scalable Machine Learning powered applications
- Experience with production grade applications preferred. Ideally with an application that leverages Machine Learning to power its decisions
- Highly motivated, individual contributor who can manage relationships in a cross-functional environment. Proven track record of working with multiple stakeholders
- Experience in creating and managing capabilities and solutions for:
Quantitative Financial Analytics
- Familiarity and experience with Cloud is a plus
- Master of Science or higher in a quantitative discipline, e.g. Data Science, Statistics, Mathematics, Computer Sciences or similar Bachelor of Science with 5 years of experience in a highly quantitative position
- High proficiency with the following technologies:
SQL / noSQL
Web Frameworks : Flask, Django
Git and GitHub
- Modeling proficiency:
Linear models & descriptive statistics
Natural Language Processing
Decision Tree Models & Boosting
Advanced time series forecasting
Linear Algebra & Spectral Methods
Deep Learning / Tensorflow / Keras
- Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with business goals.
- Performing hands-on software and strategy development, typically spending most of the time actually writing code, doing proof of concepts and conducting code reviews
- Developing deep understanding of integrations with other systems and platforms within the supported domains.
- Working with technical product managers contributing to blueprints, and assisting needs and predicting of feature sets
- Quickly generate and updating prototypes from concept to testing while soliciting feedback
- Finalizing prototypes into functional ML components and deploy on our cloud platform
- Embrace emerging standards and promoting best practices
- Demonstrate self-reliance to achieve goals collaboratively
- Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems.
- Thought leadership and innovative thinking
Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Feb 5, 2019, 1:22:19 PM