Senior Software Engineer, ML Model Serving & Real-Time Platform

Abnormal AI; United States; On-site; USD 180,000 - 259,000; Full time

Job summary

Abnormal AI is seeking a Senior Software Engineer to join the Detection Team. You will architect, deploy, and maintain model serving infrastructure, enabling real-time detection of email and cloud-based attacks while collaborating with ML and Data Science teams to improve velocity and accuracy.

The role emphasizes scalable distributed systems, cloud-native design, and hands-on leadership to drive secure, robust platform development for a world-class Detection Engine.

Qualifications

• 5+ years of experience as a Software Engineer or similar role, with hands-on ML-engineering experience.
• Experience maintaining large-scale distributed systems on cloud platforms (AWS, GCP, or Azure).
• Experience with real-time data pipelines or streaming services at high scale.
• Ability to translate requirements into actionable technical tasks and communicate progress clearly.
• Familiarity with ML workflows to support MLE teams, including serving at 50K+ QPS.

Responsibilities

• Architect, design, build, deploy, and maintain Model Serving infrastructure.
• Own projects that scale model serving and data processing to handle 10x traffic.
• Build platform to combat rapidly generated AI attacks.
• Own real-time streaming pipelines and online feature serving services.
• Build ML Training platform to improve velocity and precision.
• Collaborate with MLE and Data Science teams and distill feedback into strategy.
• Coach and mentor junior engineers through 1on1s, pair programming, and code reviews.

Skills

Distributed systems design

Real-time data pipelines

Collaboration with data science teams

Independent problem solving

Security and data privacy

Tools

AWS

GCP

Azure

Job description

Abnormal AI is seeking a Senior Software Engineer to join the Detection Team. You will architect, deploy, and maintain model serving infrastructure, enabling real-time detection of email and cloud-based attacks while collaborating with ML and Data Science teams to improve velocity and accuracy.

The role emphasizes scalable distributed systems, cloud-native design, and hands-on leadership to drive secure, robust platform development for a world-class Detection Engine.