Senior Staff Machine Learning Systems Engineer (Ads ML Platform)

Location: Remote - United States. Remote work may also be available from countries where Reddit has a physical presence.

Base salary: $292,500–$409,500 USD annually, plus potential equity and commission depending on the position offered.

Company

Reddit operates a large community platform with more than 100,000 active communities and over 100 million daily active unique visitors.

What you will do

• Own the technical strategy for the Ads ML engineer lifecycle, beginning with feature development, training data, offline experimentation, and model iteration.
• Align Ads ML platform priorities with Reddit’s broader ML Platform vision and turn Ads requirements into reusable capabilities.
• Define architecture and standards for batch and streaming computation, backfills, lineage, data quality, observability, and online/offline consistency.
• Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and self-service.
• Extend the platform strategy into model serving and online experimentation workflows.
• Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams; mentor Staff and senior engineers.

Requirements

• 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems.
• 4+ years building or operating production ML infrastructure, feature platforms, training-data systems, experimentation systems, or large-scale data pipelines.
• Experience leading broad, ambiguous, multi-team platform initiatives from strategy through adoption.
• Experience building platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.
• Deep experience with ML platforms, feature platforms, training data, experimentation, developer infrastructure, or distributed data infrastructure.
• Experience with distributed data and compute technologies such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, or Databricks.

Culture & Benefits

• Flexible workforce with remote work options and access to physical offices where available.
• Comprehensive healthcare benefits and income replacement programs.
• 401(k) with employer match and global benefit programs.
• Flexible vacation, paid volunteer time, and generous paid parental leave.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Professional development, workspace, and caregiving support.