Sift

Sift

Machine Learning Engineer

San Francisco, California

Sponsorship not specifiedDetected 1 day ago
PythonJavaScalaDistributed SystemsAlgorithmsNoSQLDatabricksGCPCloud PlatformsDockerCI/CDKafkaMachine LearningDeep LearningSparkData AnalysisData ScienceNLPMLOpsStatisticsCustomer SuccessHadoop

About the role

  • As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems.
  • You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.

Responsibilities

  • Production MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
  • System Design Mentality: Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP).
  • At Sift, we are intentionally building a diverse, equitable, and inclusive workplace.
  • This document provides transparency around how

Requirements

  • Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
  • Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.
  • Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP).
  • Solid Programming Foundations: Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
  • Distributed Systems & Big Data: Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.

Nice to have

  • Experience explicitly in the fraud detection, risk mitigation, or cyber-security domains.
  • Deep knowledge of streaming architectures (e.g., Apache Kafka).
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototyping

Compensation

  • Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly.

Benefits

  • We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need.
  • Strong Mathematical Foundations: Deep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques).

Company info

  • Sift is the AI-powered fraud platform securing digital trust for leading global businesses.
  • Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly.
  • Global brands rely on Sift to unlock growth and deliver seamless consumer experiences.
  • Visit us at sift.com http://sift.com and follow us on LinkedIn https://www.globenewswire.com/Tracker?data=XHeK0v8NcNrEkwcDe8QxwpZeCkdQqNyKlni83U-CUmrprdKXWpVlYOAbVzwe2OmlwIUN-q4HXk4hf_dazpHx2NMM1CW_SYj740q9mxXNQI4=.

This listing is sourced directly from Sift's careers page and normalized into a canonical job model.