Senior Software Engineer - Model Platform
Abnormal Security · Remote - USA
About this role
**About the Role** Abnormal AI is looking for a **Senior Software Engineer** to join the **Detection Team**. The Detection Division builds advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable—helping make the world a safer place. As a Senior Software Engineer on Detection’s **Signals and Serving Team**, you’ll help deliver feature development that is **fast, responsive, stable, and confident** for our **ML and Data Science** teams. **What you’ll bring** - A first-principles approach to building scalable, customer-centric solutions - A drive to solve meaningful, pragmatic problems for real-world people - An ownership and impact-oriented outlook - The ability to iterate in real time—solving novel problems quickly and autonomously **What you will do** - Architect, design, build, deploy, and maintain **Model Serving infrastructure** that supports a world-class Detection Engine - Own projects that scale model serving and data processing services to handle **10x** the traffic served today - Build the platform for fighting rapidly generated AI attacks - Own **real-time / near real-time streaming pipelines** and **online feature serving** services - Build Abnormal’s **ML Training platform**, improving MLE velocity and product precision/recall - Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing - Coach and mentor junior engineers through 1:1s, pair programming, high-quality code reviews, and design reviews **Must Haves** - **5+ years** of experience as a Software Engineer (or similar), with hands-on experience building **ML-engineering focused** solutions - Experience maintaining **large-scale distributed systems** on cloud platforms such as **AWS, GCP, or Azure**, with strong cloud engineering best practices - Experience maintaining **real-time and near real-time** data pipelines or streaming services at high scale - Proven ability to collaborate effectively with cross-functional teams (data scientists, ML engineers, product managers, and stakeholders). Translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback - Excellent problem-solving skills and the ability to work independently in a fast-paced environment—breaking down complex challenges and iterating while balancing immediate needs with long-term scalability - Familiarity with **machine learning workflows** to support MLE teams, including feature development/serving at **50K+ QPS**, offline/online equivalency, and large batch jobs for gathering data and training tree/deep learning models - Experience with **streaming data architectures** and real-time processing - Knowledge of **security and compliance** frameworks as they relate to data engineering and data privacy **Additional Notes** - **#LI-PP1** **About Abnormal AI’s AI-assisted recruiting** Abnormal AI uses AI-assisted tools to help the recruiting team prepare for candidate interviews (e.g., analyzing resume content and role requirements to suggest interview questions). These tools do **not** make hiring decisions or automatically screen candidates. Every decision is made by a person. If your application is successful and Abnormal AI makes a conditional offer, pre-employment checks will be completed to progress to a final offer, in line with applicable legislation and Abnormal AI policies. **Equal Opportunity Employer** Abnormal AI is an equal opportu
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