Software Engineer II

Software Engineer II

• :
• Category:
  Technology
• Position Type:
  Full Time
• Location:
  
  US-TX-Coppell

Today, through BHN’s single global platform, businesses of all kinds can tap into the world’s largest network of branded payment solutions. BHN helps businesses grow revenue, increase loyalty, motivate and reward their teams, disburse funds and engage consumers. Branded payment solutions include the issuance and distribution of gift cards, egifts, corporate payouts and rewards, along with the technology to deliver these products in seamless, integrated ways.

BHN’s network spans the globe with more than 400,000 consumer touchpoints. Learn more at

This position may be performed remotely anywhere within the United States except for the State of Alaska, North Dakota, or South Dakota. Employees located within 50 miles of a BHN office will be considered a "Hybrid" employee and are required to come into the office 2 days per week based on office schedule.

This is a hybird position that can be located in Pleasanton, CA, Coppell, TX, Portland, ME, or Seattle, WA.

Join the Data Science team s role is critical in ensuring our real-time fraud prevention systems, dynamic pricing engines, and risk models execute decisions within tight latency constraints. You will work closely with Data Scientists and ML Engineers to:

1. Take models (including XGBoost and neural networks) from experimentation to production, ensuring they are scalable, robust, and adhere to strict performance requirements. This is a highly technical role where your expertise in Java and distributed systems will directly impact the loss prevention.

2. Design, build, and maintain the high-performance, low-latency machine learning and data pipelines that underpin BHN's core business systems.

• Python-to-Java Translation (Core Function): Take analytic models and functions developed by the Data Science team in Python and accurately and efficiently translate (re-implement) them into robust Java code for use in high-performance production environments.
• Real-Time Pipeline Engineering: Design, implement, and maintain the high-availability, low-latency data and model decision pipeline
  , ensuring model scoring and risk evaluations are returned in approximately 10 milliseconds (ms).
• Backend Development: Develop and maintain scalable microservices, primarily using Java
  , to handle high-throughput model serving, API integration, and real-time risk management tools.
• Model Productionization: Work directly with Data Scientists to effectively product ionize, integrate, and tune machine learning models (e.g.,
  XGBoost, neural networks
  ).
• System Maintenance and Extension: Build, maintain, and extend technology systems that provide significant value to BHN's business, including fraud prevention systems and internal analytics tool suites.
• Process Implementation: Drive the implementation of tactical pricing initiatives and strategy changes, addressing complex backend process and technical requirements.
• Cloud Operations: Utilize expertise with Amazon Web Services (AWS) or similar cloud platforms to ensure systems are deployed, monitored, and scaled efficiently.
• Collaboration: Work closely with data scientists, ML engineers, and product managers to define technical requirements and provide inputs to the overall systems roadmap.

• Education: Bachelor’s degree in Computer Science, Software Engineering, Mathematics, Physics, or a related analytical field.
• Experience: +2 years of experience developing and maintaining high-performance backend systems or real-time data/ML infrastructure in an engineering role.
• Core
  
  Languages:
  
  
  Strong, demonstrable proficiency in Java is essential for high-throughput, low-latency service development.
• Secondary
  
  Languages:
  
  Proficiency in Python for understanding, debugging, and translating ML code and data science prototypes.
• ML Comfort: Comfort with the structure and deployment of machine learning models and statistical modeling techniques, including algorithms like XGBoost and neural networks
  .
• Systems Expertise: Experience building robust systems at scale on top of Amazon Web Services (AWS) or similar cloud services.
• Pr…