Software Engineer, Abnormal Security

• Experience in Python, Spark, Databricks, Airflow, Django, Postgres
• Experience building data pipelines using PySpark
• Experience in “large-scale” solutions or environments with complex integrations, latency requirements, or throughput challenges
• Performance debugging and benchmarking
• Proven experience translating business requirements into software requirements and explaining the systems design
• Proven experience working effectively with cross-functional teams
• BS degree in Computer Science, Applied Sciences, Information Systems or other related engineering field
• 2+ years of professional production experience in fullstack developmen

Desirable

• This position represents a unique opportunity to contribute significantly to our mission of providing unparalleled detection capabilities worldwide
• The team’s mission revolves around empowering our detection team with high-quality data and cutting-edge tools, ensuring that all misclassifications can be easily assessed and analyzed
• The strategic approach encompasses the development of essential detection tools, improved misclassification comprehension, and enhanced communication with customers
• Core components the team owns include the rule based email detection engine, LLM system for automated message labeling, analysis tools for misclassification understanding and flow comprehension, data quality for ML model analysis and training and the platform for customer interaction of detection concerns
• Enhance the speed and quality of detection systems development
• Power pipelines to process and respond to customer feedback responsibly
• Supply detection teams with top-notch, accurate data used for evaluating and training ml models
• Automate processes to improve customer responses
• Develop, design, modify, and test systems for enhanced data quality and understanding
• Collaborate with Technical Program Managers, Product Managers, Data Engineers, Data Scientists, and operational and engineering teams to implement, verify, and iterate on product development
• Exercise sound judgment in selecting methods and techniques for problem-solving
• Writes code with testability, readability, edge cases, and errors in mind
• Writes and reviews technical design documents