Software Engineer Ii (Dss Scoring Infrastructure)

About You

As a software engineer on Detection Serving & Signals, focused on our Scoring Infrastructure, you will be responsible for developing and owning the ML scoring services which allow for the operation of the abnormal Detection engine.

We are looking for software engineers with the following qualities:

• An ability to iterate in real-time - solving novel problems, quickly and autonomously
• A "mission-first" drive to solve meaningful & pragmatic problems for real-world people
• An "ownership" & "impact" oriented outlook on your efforts and growth
• A “principle-first” approach to building scalable, customer-centric solutions

In This Job, You Will Bring These Skills

• At least 3 years of experience working as a Software Engineer
• Familiarity with developing in a Cloud Native architecture, particularly experience with AWS and Azure
• Familiarity with containerization and deployment platforms like Docker, AWS, ECS, and Kubernetes
• Nice-to-have: Experience with ML open source libraries such as Tensorflow, Pytorch, ONNX
• Familiarity with web serving frameworks/patterns like Bottle/Gunicorn, Django, and/or Finagle
• Experience with stream-processing technologies: Kafka, Spark structured streaming
• Ability to use Python and/or Go in development
• Familiarity with serialization libraries like Thrift or Protobuf
• Nice-to-have: Experience developing MLOps architecture, such as Feature Stores and ML inference engines
• Role-specific skills:

Role Responsibilities

• Drive successful adoption and feedback-gathering of Scoring Infra solutions across MLE teams
• Collaborate closely with MLE (Message Detection, Cloud Unity) to identify pain points and use-cases and incorporate into a multi-month roadmap for ownership areas
• Architect, design, build, and deploy real-time backend scoring services that support the Detection engine
• Collaborate with Platform & Infrastructure teams to identify & execute on directionally correct ways of scaling out Detection infra and the technologies we should be adopting