Senior Software Engineer – Model Platform

Abnormal Security

. Architect, design, build, deploy, and maintain Model Serving infrastructure supporting the Detection Engine .

Posted 9/18/2026full-timeRemote • United States, CanadaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining large-scale distributed systems and real-time data pipelines, with a strong focus on machine learning engineering solutions. Proven ability to collaborate with cross-functional teams and mentor junior engineers while driving projects that enhance model serving infrastructure.

Highest-signal resume keywords

Large-Scale Distributed SystemsReal-Time Data PipelinesMachine Learning EngineeringCloud Platforms (AWS, GCP, Azure)Feature Development and Serving

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning WorkflowsStreaming Data ArchitecturesData Processing ServicesModel Serving InfrastructureFeature Serving ServicesData Gathering and TrainingProblem-SolvingTechnical Task TranslationCode ReviewsDesign Reviews

Soft Skills

CollaborationMentoringCommunicationAdaptabilityIndependence

Industry Keywords

Data PrivacySecurity FrameworksCompliance FrameworksAI AttacksHigh Scale Processing

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud Platform

About the role

Key responsibilities & impact

Architect, design, build, deploy, and maintain Model Serving infrastructure supporting the Detection Engine
Own projects scaling model serving and data processing services to handle 10x current traffic
Build the platform for fighting rapidly generated AI attacks
Own real-time and near real-time streaming pipelines and online feature serving services
Build Abnormal’s ML Training platform to improve MLE velocity and product precision and recall
Collaborate 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, code reviews, and design reviews

Requirements

What you’ll need

5+ years of experience as a Software Engineer or in a similar role, with hands-on experience building ML-engineering focused solutions
Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure
Strong grasp of cloud-based engineering best practices
Experience maintaining real-time and near real-time data pipelines or streaming services at high scale
Ability to collaborate effectively with data scientists, machine learning engineers, product managers, and other stakeholders
Ability to translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback
Excellent problem-solving skills and ability to work independently in a fast-paced environment
Familiarity with machine learning workflows and requirements supporting MLE teams
Experience with feature development and serving at 50K+ QPS
Knowledge of offline/online equivalency and large batch jobs for data gathering and training tree and deep learning models
Experience with streaming data architectures and real-time processing
Knowledge of security and compliance frameworks related to data engineering and data privacy

Benefits

Comp & perks

Equal opportunity employer
Pre-employment checks in line with prevailing legislation and Abnormal AI's security and privacy standards