Machine Learning Software Engineer

Job Overview

RESPONSIBILITIES:

Kforce has a client in building a team of Machine Learning Software Engineers in Wilmington, Delaware (DE) and Tampa, Florida (FL) and Plano, Texas (TX). This team is focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers. Summary: Our Machine Learning Software Engineers will have the business acumen to understand and analyze problems, define and test hypotheses and develop Machine Learning frameworks and best practices. Additionally, they will be responsible to intricate knowledge of our business domains and data sets which include Systems of Record (SOR), historical and external data. Finally, this individual will take ownership in designing models to deliver performance and accuracy when operationalized as well as inference engines at scale with the business processes and applications. Duties:

• Analyze and conduct learning/simulations with large datasets combining multiple platforms (ex. Hadoop, Spark, AWS), and machine learning frameworks (ex. R, sci-kit, PySpark, Pandas, TensorFlow)
• Lead/mentor a team of data scientists and machine learning engineers, who help the business identify new insights from large/rich data sets, and implement data driven strategies that reduces fraud, post-fraud loss and other operational efficiencies

Job Requirements:

REQUIREMENTS:

• 3+ years of hands-on experience: Python (or other scripting), Java, Hadoop/Spark/Hive and/or AWS, and 10+ years of hand-on experience with SQL
• Expertise across application, data and infrastructure architecture disciplines
• Advanced knowledge of architecture, design and business processes
• Experience with Machine Learning, Deep Learning, Data Mining, and/or Statistical Analysis tools
• Operationalize machine learning models using offline and online models, model performance monitoring, frequent/automated model updates, back/now testing, managed test harness and managed feature libraries; Ability to automate data exploration and model exploration activities and embed end-to-end model development and deployment into automated CI-CD/DevOps pipelines
• Hands-on data analytics using machine learning, statistical modelling and/or data mining to uncover insights from large data sets and develop data and predictive models supporting multiple business domains spanning Fraud, Consumer Banking Operations, Digital Banking and Customer Experience scenarios. Interpret and explain methods using statistical analysis

Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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