Software Engineer - Ads ML Features Platform
Reddit has a flexible first workforce! if you happen to live close to our physical office location our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the Netherlands or the United Kingdom.
Team Overview
We’re building a scalable feature platform that powers Ads ML by making high-quality features easy to build, share, and maintain. Our small but growing team works on projects like batch feature management, impression feature store, training set generation, and event-driven features—with streaming feature management on the horizon.
We are looking for an engineer with deep experience in building high-scale data infrastructure and ML platforms to help evolve and scale our feature management systems.
What You’ll Do
Design and build data infrastructure that supports large-scale feature computation, transformation, and storage.
Develop frameworks for batch and event-driven features with a focus on reliability, scalability, and ease of use.
Drive improvements in data quality and governance through validation, anomaly detection, drift monitoring, and feature lineage tracking.
Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.
Contribute to training set generation pipelines and ensure reproducibility and feature versioning for model development.
Help shape the future of the platform by exploring streaming feature management and other next-gen capabilities.
What You Bring
5+ years in infrastructure/platform engineering or large-scale distributed systems.
2+ years hands-on experience with SQL-based cloud data warehouses (e.g., BigQuery, Snowflake, Redshift, Databricks)
Proficiency with large-scale feature computation frameworks (Spark, PySpark, or Scala).
Expertise in distributed systems (scaling, partitioning, fault tolerance, caching).
Familiarity with ML production systems, especially ML feature platforms, is a big plus
Knowledge of MLOps workflows – from feature engineering to training to online serving
Benefits:
Private Pension plan with Employer-matching
100% employer-sponsored group medical plan
Income Replacement Programs
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Reddit Global Days Off
Software Engineer - Ads ML Features Platform
Reddit has a flexible first workforce! if you happen to live close to our physical office location our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the Netherlands or the United Kingdom.
Team Overview
We’re building a scalable feature platform that powers Ads ML by making high-quality features easy to build, share, and maintain. Our small but growing team works on projects like batch feature management, impression feature store, training set generation, and event-driven features—with streaming feature management on the horizon.
We are looking for an engineer with deep experience in building high-scale data infrastructure and ML platforms to help evolve and scale our feature management systems.
What You’ll Do
Design and build data infrastructure that supports large-scale feature computation, transformation, and storage.
Develop frameworks for batch and event-driven features with a focus on reliability, scalability, and ease of use.
Drive improvements in data quality and governance through validation, anomaly detection, drift monitoring, and feature lineage tracking.
Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.
Contribute to training set generation pipelines and ensure reproducibility and feature versioning for model development.
Help shape the future of the platform by exploring streaming feature management and other next-gen capabilities.
What You Bring
5+ years in infrastructure/platform engineering or large-scale distributed systems.
2+ years hands-on experience with SQL-based cloud data warehouses (e.g., BigQuery, Snowflake, Redshift, Databricks)
Proficiency with large-scale feature computation frameworks (Spark, PySpark, or Scala).
Expertise in distributed systems (scaling, partitioning, fault tolerance, caching).
Familiarity with ML production systems, especially ML feature platforms, is a big plus
Knowledge of MLOps workflows – from feature engineering to training to online serving
Benefits:
Private Pension plan with Employer-matching
100% employer-sponsored group medical plan
Income Replacement Programs
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Reddit Global Days Off