Software Engineer II, Model Platform

Abnormal AI, Inc.

$110K — $130K *
US-AnywhereRemote in Canada
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years of experience as a Software Engineer or similar role, focusing on data solutions.
  • Proficient in leveraging AI tools for effective software system development.
  • Experience managing large-scale distributed systems on cloud platforms like AWS, GCP, or Azure.
  • Hands-on with real-time and near real-time data pipelines or streaming services.
  • Solid understanding of computer science fundamentals, data structures, and performance optimization.
  • BS in Computer Science, Applied Sciences, Information Systems, or related engineering field.

Responsibilities

  • Leverage AI tools to architect, design, and maintain Model Serving infrastructure.
  • Own projects that scale model serving and data processing services for higher traffic.
  • Manage real-time and near real-time streaming pipelines and online feature serving services.
  • Collaborate with Machine Learning Engineers and Data Science teams to align strategies and feedback.
  • Execute efficiently on feedback to enhance system functionality.

Benefits

  • Flexible work arrangements to support work-life balance.
  • Collaborative team environment focused on innovation and technology.
  • Opportunities for professional development and growth.
  • Participation in cutting-edge AI projects with significant impact.
  • Inclusive culture that values diverse perspectives and experiences.
Full Job Description
About the Role

Abnormal AI is looking for a Software Engineer II to join the Detection Team. The Detection Division is focused on building the world's most advanced technology to identify and stop email and cloud-based attacks that were previously undetectable, helping make the world a safer place. As a Software Engineer focused on building systems for Detection's Model Platform, you will be responsible for making feature development at Abnormal a fast, responsive, stable, and confident experience for our ML and Data Science teams.

The ideal candidate brings a first-principles approach to building scalable, customer-centric solutions, an ownership-oriented mindset, and the ability to iterate quickly and autonomously on novel problems.
What You Will Do
  • Leverage industry-standard AI tools to architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine.
  • Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today.
  • Own real-time and near real-time streaming pipelines, and online feature serving services.
  • Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing.
Must Haves
  • 4+ years of experience as a Software Engineer or in a similar role, with hands-on experience building data-focused solutions.
  • Proficiency leveraging AI tools to accelerate engineering outcomes through discovery, design, implementation, and rollout of software systems.
  • Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of best practices in cloud-based engineering.
  • Experience with real-time and near real-time data pipelines or streaming services.
  • Strong fundamentals in computer science, data structures, and performance optimization.
  • BS degree in Computer Science, Applied Sciences, Information Systems, or other related engineering field.
Nice to Have
  • Familiarity with our stack: AWS, Kubernetes, Python/Django, Golang, and Postgres.
  • Experience building scalable, enterprise-grade applications.
  • Experience with web security (e.g., OWASP Top 10).
  • Familiarity with AI development tools such as Cursor, GitHub Copilot, or Claude.

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AI and our hiring process
Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and identify areas for the interviewer to explore. They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person.

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