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Software Engineer, Machine Learning Platform
Posted on 11/19/2021
San Francisco, CA, USA
Experience Level
Desired Skills
Apache Spark
Data Analysis
Data Science
Google Cloud Platform
  • 2+ years of professional software development experience or a degree in CS (or a related field) with 2+ years of experience
  • Experience building highly available low-latency systems using Java, Scala, C++ or other object-oriented languages
  • Experience working with large datasets and best in class data processing technologies for both stream and batch processing, such as Apache Spark, Apache Beam, MapReduce
  • Strong debugging, testing, tuning, and problem-solving skills
  • Strong communication & collaboration skills, and a belief that team output is more important than individual output
  • Self-starter, with a quick learning curve
  • Design and build tools and processes to make the release of new machine learning models fast, easy, safe, and minimally disruptive
  • Participate in architecture discussions to meet the requirement to serve hundreds of machine learning models at thousands of queries per second
  • Ensure that our systems can continue to scale rapidly while addressing rapidly evolving product team needs
  • Implement scalable, low-latency, high-throughput, fault-tolerant, extensible, and easily maintainable data processing pipelines for both batch and real-time systems
  • Motivate, listen and empathize, and help engineers and data scientists to excel
Desired Qualifications
  • Familiarity with practical challenges in ML systems such as feature extraction and definition, data validation, training, monitoring, and management of features and models
  • Practical knowledge of how to build end-to-end ML workflows
  • Experience with building an ML feature store for batch and real-time aggregation/serving
  • Knowledge of GCP or AWS cloud stack for web services and big data processing

201-500 employees

Fraud prevention platform
Company Overview
Sift aims to help everyone trust the internet
Company Core Values
  • Connect the dots
  • Trust and Safety for All
  • Get Sift Done