Senior Software Engineer - Model Platform

<h2>About the Role</h2> <p>Abnormal AI is looking for a Senior Software Engineer to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology for identifying and stopping email and cloud-based attacks that were previously undetectable and helping make the world a safer place. As a Senior Software Engineer building systems for Detection’s Signals and Serving Team, you will make feature development at Abnormal fast, responsive, stable, and confident for our ML and Data Science team.</p> <p>The ideal candidate would have the following qualities:</p> <ul> <li>A first principles approach to building scalable, customer-centric solutions</li> <li>A drive to solve meaningful & pragmatic problems for real-world people</li> <li>An ownership and impact-oriented outlook on your efforts and growth</li> <li>An ability to iterate in real-time-solving novel problems, quickly and autonomously</li> </ul> <p>An ability to iterate in real-time - solving novel problems, quickly and autonomously</p> <h2>What you will do </h2> <ul> <li>Architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine</li> <li>Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today</li> <li>Build the platform for fighting against rapidly generated AI attacks</li> <li>Own real-time, near real-time streaming pipelines, and online feature serving services</li> <li>Build Abnormal’s ML Training platform, improving MLE velocity and product precision and recall</li> <li>Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing</li> <li>Coach and mentor junior engineers via 1on1s, pair programming, high-quality code reviews, and design reviews</li> </ul> <h2>Must Haves </h2> <ul> <li><strong>5+ years of experience</strong> as a Software Engineer or in a similar role, with hands-on experience in building ML-engineering focused solutions.</li> <li>Experience maintaining<strong> large-scale distributed systems on cloud platforms</strong> such as AWS, GCP, or Azure, including a strong grasp of cloud-based engineering best practices.</li> <li>Experience with maintaining <strong>real-time and near real-time</strong> data pipelines or streaming services at high scale</li> <li><strong>Proven ability to collaborate effectively</strong> with cross-functional teams, including data scientists, machine learning engineers, product managers, and other stakeholders. You can translate requirements into actionable technical tasks, communicate progress clearly, and adapt to feedback.</li> <li><strong>Excellent problem-solving skills</strong> and the ability to work independently in a fast-paced environment. You can break down complex challenges into manageable steps and iterate on solutions, balancing immediate needs with long-term scalability.</li> <li>Familiarity with <strong>machine learning</strong> workflows and requirements to support MLE teams effectively. This includes feature development and serving at 50K+ QPS, offline/online equivalency, large batch jobs for data gathering and training of tree and deep learning models.</li> <li>Experience with <strong>streaming data architectures</strong> and real-time processing.</li> <li>Knowledge of <strong>security and compliance</strong> frameworks as they relate to data engineering and data privacy.</li> </ul> <p>#LI-PP1</p><div class="content-conclusion"><p>&l