Senior Software Engineer, Machine Learning

Summary

Join Sift, a leading AI-powered fraud prevention platform, and contribute to the development of advanced machine learning models to combat fraud at scale. You will be responsible for researching and applying cutting-edge machine learning algorithms, building offline experimentation systems, and scaling machine learning pipelines. This role requires a strong understanding of machine learning and data science concepts, along with experience working with production ML systems, large datasets, and backend systems. You will collaborate with other teams to build new ways to use machine learning within Sift and generate actionable insights for customers to prevent fraudulent behaviors and transactions.

Requirements

• Practical understanding of machine learning and data science concepts, and a track record of solving problems with these methods
• 4+ years of experience working with production ML systems
• 3+ years experience working with large datasets using Spark, MapReduce, or similar technologies
• 5+ years experience building backend systems using Java, Scala, Python, or other language
• Experience training machine learning models end-to-end
• Strong communication & collaboration skills, and a belief that team output is more important than individual output
• Degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, or a related field

Responsibilities

• Research and apply the latest machine learning algorithms to power our core business product
• Build offline experimentation systems used to evaluate tens of thousands of models simultaneously
• Work on evolving Sift’s ML models and architecture
• End-to-end design & prototyping of a wide range of technologies
• Scale machine learning pipelines are used to produce thousands of models derived from terabytes of data
• Build systems that automatically explain how a model arrived at a prediction
• Use data science techniques to analyze fraudulent behavior patterns
• Collaborate with other teams to build new ways to use machine learning within Sift
• Generate and execute ideas to provide customers with meaningful and actionable insights to identify and prevent fraudulent behaviors and transactions
• Leverage anomaly detection algorithms to identify unusual behaviors for customer traffic patterns

Preferred Qualifications

• Experience working with scalable, real-time prediction systems in production
• Familiarity with multiple machine learning or statistical packages in Python or another programming language
• Advanced degree in Statistics, Machine Learning, Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, or a related field