[Remote] Machine Learning Engineer

Note: The job is a remote job and is open to candidates in USA. Sift is the AI-powered fraud platform securing digital trust for leading global businesses. As a Machine Learning Engineer, you will bridge the gap between data science and large-scale distributed systems, building end-to-end pipelines and maintaining an automated machine learning ecosystem.ResponsibilitiesModel Development & Refinement: Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real timeFeature Engineering at Scale: Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognitionProduction MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained modelsSystem Optimization: Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databasesCollaborative Innovation: Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutionsSkills4+ years of professional experience building and deploying large-scale machine learning models into high-traffic production environmentsStrong 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 BigtableDeep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques)Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (GCP)Experience explicitly in the fraud detection, risk mitigation, or cyber-security domainsDeep knowledge of streaming architectures (e.g., Apache Kafka)Familiarity with containerization and orchestration tools like Docker and KubernetesFamiliarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototypingBenefitsOffers EquityRemoteCompany OverviewSift applies insights from a global network of data to detect fraud and increase positive user experience. It was founded in 2011, and is headquartered in San Francisco, California, USA, with a workforce of 201-500 employees. Its website is http://sift.com.Company H1B SponsorshipSift has a track record of offering H1B sponsorships, with 3 in 2026, 12 in 2025, 10 in 2024, 12 in 2023, 16 in 2022, 13 in 2021, 13 in 2020. Please note that this does not guarantee sponsorship for this specific role.