Machine Learning Engineer 2

• Contributes to the implementation, refinement and validation of machine learning algorithms for products and applications.
• Trains machine learning models, validates the accuracy of the machine learning models once trained and deploys validated machine learning models into production.
• Contributes to designs and development of data pipelines consisting of data ingest, data validation, data cleaning and data monitoring.
• Researches, writes and edits documentation and technical requirements, including evaluation plans, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs) and other intellectual property.
• Contributes to the testing and evaluation of solutions presented to the Company by various internal and external partners and vendors. Contributes to case studies, testing and reporting.
• Designs proof of concept solutions and contributes to studies to support future product or application development.
• Consistent exercise of independent judgment and discretion in matters of significance.
• Regular, consistent and punctual attendance. Must be able to work nights and weekends, variable schedule(s) and overtime as necessary.
• Other duties and responsibilities as assigned.

Employees at all levels are expected to:

• Understand our Operating Principles; make them the guidelines for how you do your job.
• Own the customer experience - think and act in ways that put our customers first, give them seamless digital options at every touchpoint, and make them promoters of our products and services.
• Know your stuff - be enthusiastic learners, users and advocates of our game-changing technology, products and services, especially our digital tools and experiences.
• Win as a team - make big things happen by working together and being open to new ideas.
• Be an active part of the Net Promoter System - a way of working that brings more employee and customer feedback into the company - by joining huddles, making call backs and helping us elevate opportunities to do better for our customers.
• Drive results and growth.
• Respect and promote inclusion & diversity.
• Do what's right for each other, our customers, investors and our communities.