Senior Software Engineer – Model Platform

Abnormal Security

. Architect, design, build, deploy, and maintain Model Serving infrastructure supporting a world-class Detection Engine .

Posted 9/18/2026full-timeRemote • 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 on cloud platforms, with a strong focus on machine learning engineering practices. 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 PipelinesCloud Platforms (AWS, GCP, Azure)Machine Learning Engineering SolutionsMentoring Junior Engineers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model Serving InfrastructureData Processing ServicesMachine Learning WorkflowsStreaming Data ArchitecturesFeature Development and ServingTree and Deep Learning ModelsCloud-Based Engineering Best PracticesHigh-Scale Data ProcessingTechnical Task TranslationProblem-Solving

Soft Skills

CollaborationCommunicationAdaptabilityCoachingMentoring

Industry Keywords

Data PrivacySecurity FrameworksCompliance FrameworksAI AttacksCross-Functional Teams

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud Platform

About the role

Key responsibilities & impact

Architect, design, build, deploy, and maintain Model Serving infrastructure supporting a world-class 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-on-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 cross-functional teams, including 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, including feature development and serving at 50K+ QPS, offline/online equivalency, and large batch jobs for data gathering and training of 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

Pre-employment checks for successful candidates, in line with prevailing legislation and Abnormal AI's security and privacy standards
Equal opportunity employment