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Machine Learning Engineer

SiftSan Francisco, CaliforniaEngineering
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Salary
$140K – $190K
Job type
Full-time
Work mode
Remote
Posted
20 Jul 2026
Status
Open · checked 7d ago

About this role

Sift seeks a Machine Learning Engineer to join the engineering department in San Francisco, California, with remote flexibility. This full-time position suits professionals with at least four years of experience who want to connect data science with large-scale distributed architecture.

Role Overview

In this position, the professional designs and implements end-to-end pipelines that extract signals, build custom models for individual merchants, and deliver predictions at production scale with minimal latency. The work involves an automated machine learning ecosystem that continuously updates models utilizing streaming global telemetry data.

Key Responsibilities

Design, construct, and release online machine learning models, covering ensemble methods, deep learning, transformer architectures, and graph-based models, to identify emerging fraud threats in real time.
Construct high-frequency time-series features sourced from over one trillion behavioral events, tuning for rapid signal extraction and pattern recognition.
Operate, maintain, and upgrade automated model training and deployment infrastructure to guarantee smooth continuous integration and deployment of updated models.
Author high-performance software code to reduce runtime scoring latency, ensuring core machine learning services scale across distributed databases.
Partner alongside Core Infrastructure, Product Management, and Data Science teams to convert business fraud trends into algorithmic defenses.

Requirements

Four or more years of professional background creating and releasing large-scale machine learning models into high-traffic production settings.
Solid programming expertise in Java or Scala for production backend systems, alongside Python for data analysis and model prototyping.
Practical background using Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, as well as NoSQL databases such as Bigtable.
Strong grounding in statistics, probability, and standard machine learning approaches including XGBoost, Random Forests, Neural Networks, and clustering methods.
Analytical system design mindset regarding data consistency, pipeline failures, and performance limits within a distributed, multi-tenant Google Cloud Platform environment.

Nice to Have

Practical background explicitly working in fraud detection, risk mitigation, or cybersecurity spaces.
Advanced familiarity with streaming architectures like Apache Kafka.
Knowledge of containerization and orchestration platforms such as Docker and Kubernetes.
Familiarity utilizing AI coding assistants like Claude Code to speed up development and model prototyping.

Skills and Tools

Python, Java, Scala
GCP, Bigtable, Databricks
Apache Spark, Apache Flink, Hadoop, Apache Kafka
Docker, Kubernetes, MLOps
Machine learning, deep learning, NLP, statistical modeling

Salary and Benefits

Annual salary range between $140,000 and $190,000 in USD.
Full-time employment status.

About the Company

Sift operates as an AI-powered fraud platform designed to secure digital trust for major global enterprises. By investing heavily in machine learning and user identity, alongside a data network processing one trillion events annually, the company empowers more than 700 customers to expand fearlessly. Sift is intentionally focused on building a diverse, equitable, and inclusive workplace that champions authentic experiences and innovation.

How to Apply

Interested candidates should visit the official Sift careers page at sift.com to submit an application for this role.

Skills and tech stack

PythonKubernetesDockerGCPSparkJavaMLOpsDeep LearningMachine LearningKafkaScalaDistributed Systems

Questions candidates ask

What is the salary range for the Machine Learning Engineer role?

The annual salary range for this position is between $140,000 and $190,000 USD.

Where is this job located?

The role is based in San Francisco, California, with remote work options available.

How much experience is required for this position?

Candidates must have four or more years of professional experience building and deploying large-scale machine learning models into high-traffic production environments.

What programming languages are required?

Strong proficiency in Java or Scala for backend production systems, as well as Python for data analysis and model prototyping, is required.

What cloud platform and big data tools are used?

The role utilizes the Google Cloud Platform, Databricks, NoSQL data stores like Bigtable, and big data processing frameworks such as Apache Spark, Apache Flink, or Hadoop.

Ready to apply?

The application is on the official Sift careers page.

Apply on company site