Machine Learning Systems Engineer (Ads ML Platform)

Role Overview

Machine Learning Systems Engineer for Reddit’s Ads ML platform. You’ll build scalable, reliable infrastructure and developer-facing tools that enable ML feature engineering workflows in production.

Key Missions / Responsibilities

• Design and build data infrastructure supporting large-scale feature computation and transformation, training set computation, and storage.
• Develop batch and real-time feature frameworks focused on reliability, scalability, and usability.
• Build feature governance capabilities, including:
  • lineage tracking
  • validation and drift detection
  • anomaly monitoring
  • reproducibility
  • versioning
• Partner with ML engineers to integrate feature engineering workflows into ML production systems.

Requirements

• 3+ years in data infrastructure/platform engineering or ML infrastructure platforms.
• Strong coding skills with ability to write clean, maintainable, and well-tested code.
• Familiarity with ML data workflows such as:
  • feature generation
  • training dataset creation
  • batch processing and real-time data processing
  • experimentation and online serving
• Hands-on experience building production services, data pipelines, APIs, workflow systems, or developer tools.
• Experience with at least one distributed data/compute system, such as:
  • Spark / PySpark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery (or similar).

Nice-to-Haves

• Experience building intelligent automation/agentic workflows for ML systems.
• Experience across MLOps workflows (feature engineering, training pipelines, experimentation, model deployment, online serving).