Software Engineer II - Machine Learning Infrastructure

About The Role

Abnormal Security is looking for a Software Engineer to join the Detection Team, working on projects that advance our Message Processing, Model Inference systems, and ML Infrastructure to 5x Scale. 

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 an Engineer focused on building the Platform for our Email Detection Engine, you’ll leverage your experience with high scale, distributed systems to build resilient solutions that solve critical problems such as:

• Providing low latency live scoring for emails at 50k+ QPS
• Evolving our ML inference systems to power computationally intensive LLMs and other complex models
• Ensuring that we have highly available signals, generated and served within tight SLA

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The ideal candidate has the following qualities: 

• 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 on your efforts and growth
• An ability to iterate in real-time-solving novel problems, quickly and autonomously

What You Will Do 

• Architect, design, build, and deploy backend services and infrastructure that support a world-class Detection Engine
• Ownership of projects that enable us to meet ambitious goals for, such as building the plan to scale components of Detection’s ML Platform, such as our Behavioral Aggregate Systems, by 10x 
• Collaborate closely with MLE teams, by distilling feedback, correlating it to our strategy, and executing
• Enhance your engineering expertise and develop new skills by collaborating with world-class engineers

Must Have

• 2-5 years of professional experience as a hands-on engineer building data-oriented products
• Experience with real-time, online, and/or high-throughput & low-latency distributed systems
• Works well with other stakeholders - has worked with cross-functional teams to drive projects over the finish-line
• High standards - sets high standards and expectations for project execution for themselves and for collaborators

Nice To Have 

• MS degree in Computer Science, Electrical Engineering or other related engineering field
• Experience building ML systems/products
• Knowledge of key ML Ops team technologies (Spark, Data platform and Data coordination, Hadoop, Hive, feature platform serving systems, ML training and ML serving platforms, etc.)
• Experience with big data or statistics 
• Experience in ML development
• Familiarity with cyber security industry

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