Machine Learning Engineer

Location: VA Vienna - Headquarters Full/Part Time: Full-Time Regular/Temporary: Regular

Job Description

YOUR LIFE'S MISSION: POSSIBLE

You have goals, dreams, hobbies and things you’re passionate about.


What’s Important to You Is Important to Us
We’re looking for people who not only want to do meaningful, challenging work, keep their skills sharp and move ahead, but who also take time for the things that matter to them—friends, family and passions. And we're looking for team members who are passionate about our mission—making a difference in military members' and their families' lives. Together, we can make it happen.


Don’t take our word for it.

  • FORTUNE 100 Best Companies to Work For®
  • Computerworld® Best Places to Work in IT
  • FORTUNE® Best Workplaces for Millennials
  • Forbes® America’s Best Employers

Basic Purpose

Drive significant impact and value through the design and management of machine learning (ML) ETL processes, architecture, and data modeling to promote machine learning at scale. Collaborate closely with the data science and other development teams to ensure model productionalization is scalable repeatable, and automatable. Partner with internal stakeholders to understand business and technical needs. Communicate and present complex analytics results and concepts to leadership and internal stakeholders. Stay current on cutting edge research for ML and AI technology and concepts. Is an individual contributor working both in a team and on individual assignments. May assist with leading broader longer term efforts.

Responsibilities:

• Lead the use of data to drive machine learning ETL pipeline design, architecture, data modeling, and machine learning at scale
• Code and develop software that deploys machine learning models and algorithms into production
• Perform data ETL, statistical and analytical analyses, and communicate insights and recommendations to internal and external clients
• Perform algorithmic analysis to optimize runtime performance and other improvements
• Discover patterns in complex structured and unstructured data and optimize ETL processes
• Leverage machine learning algorithms to optimize and deliver results by reducing computational complexity and increasing the accuracy of models and improving on business metrics.
• Drive insights and work through the lifecycle of delivering and scaling of these insights into Production
• Implement strategies to assess data quality throughout the software development life cycle
• Advise on best practices for software engineering for data applications with an emphasis on statistical modeling, machine learning, advanced analytics, and/or Artificial Intelligence
• Design data models or feature stores around complex, large-scale data for machine learning use cases
• Employ AI and/or ML that may include natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR)
• Create a data-driven culture, driving business decisions via insights from data
• Identify and compare technologies to address new enterprise needs, especially around performing machine learning at scale
• Coach and mentor project team members in carrying out day-to-day production support activities
• Lead or participate in the preparation of high quality project deliverables that are valued by the business and present them in such a manner that they are easily understood by project stakeholders
• Perform other duties as assigned

Qualifications and Education Requirements:

• Master’s degree in Computer Science, Statistics, Engineering or related field, or the equivalent combination of education, training and experience
• Experience in designing and implementing large scale data loading, manipulation, processing, exploration solutions using Hadoop/NoSQL technologies etc.
• Background in machine learning, distributed systems design, statistics, or quantitative analysis
• Experience working with raw as well as prepared structured and unstructured data
• Working knowledge of Apache Spark, PySpark, Azure Data Factory, Azure Databricks, Azure DevOps, Azure ML (Machine Learning), Hadoop, Hive (Apache), Informatica, Microsoft Azure, Microsoft Power BI, Microsoft SharePoint, Microsoft SQL Server, MS Office Products Operation Data Integration (OLTP), Teradata and Python
• Significant experience in developing sophisticated algorithms to automate processes and tasks
• Advanced knowledge of current AI and ML technologies and concepts
• Understands enterprise data strategies and tools used for vast solutions
• Significant experience communicating and presenting complex analytics results and concepts to leadership and internal stakeholders
• Demonstrates change management and/or excellent communication skills

Desired Qualifications and Education Requirements:

• Knowledge of Navy Federal Credit Union instructions, standards, and procedures

Hours:
Monday - Friday, 8:00am - 4:30pm

Remote Work Policy: Remote work is available for all positions contingent on business need and manager discretion

Equal Employment Opportunity

Navy Federal values, celebrates, and enacts diversity in the workplace.  Navy Federal takes affirmative action to employ and advance in employment qualified individuals with disabilities, disabled veterans, Armed Forces service medal veterans, recently separated veterans, and other protected veterans.  EOE/AA/M/F/Veteran/Disability


Disclaimer

Navy Federal reserves the right to fill this role at a higher/lower grade level based on business need.
An assessment may be required to compete for this position.


Bank Secrecy Act

Remains cognizant of and adheres to Navy Federal policies and procedures, and regulations pertaining to the Bank Secrecy Act.