Senior Staff Machine Learning Systems Engineer, Ads ML Platform

Reddit is seeking a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus is on the feature development and training iteration loop, making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, the scope expands into serving and online experimentation workflows.

• Own the technical strategy for the end-to-end Ads ML engineer lifecycle, starting with feature development, training data, offline experimentation, and model iteration workflows.
• Align Ads ML platform priorities with Reddit’s broader ML Platform vision, translating Ads pain points into reusable platform capabilities.
• Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.
• Build platform abstractions and workflow automation to make ML development faster, safer, more reliable, and more self-service.
• Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership and drive execution.
• Mentor Staff and senior engineers, raising the architecture and operational bar.

• 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.
• Deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.
• Experience with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar.
• Ability to influence senior engineers and leaders through technical reasoning, RFCs, design reviews, and decision frameworks.

Base salary range: $292,500—$409,500 USD. Eligible for equity in the form of restricted stock units. Benefits include comprehensive healthcare, 401k with employer match, flexible vacation, paid parental leave, family planning support, gender-affirming care, mental health coaching, and more.

Apply via the provided Greenhouse link.