Senior Machine Learning Engineer, Ads ML Platform

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We’re building a scalable feature platform that powers Ads ML by making high-quality features and training datasets easy to build, share, and maintain. Our small but growing team works on projects like batch & realtime feature management platform, training set generation platform, sequence features platform and, agentic and automated ML workflows for feature lifecycle management.

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.

• →Design and build data infrastructure that supports large-scale feature and training set computation, transformation, and storage.
• →Develop frameworks for batch and real-time features with a focus on reliability, scalability, and ease of use.
• →Build platform capabilities for feature governance, including lineage tracking, validation, drift detection, anomaly monitoring, reproducibility, and versioning
• →Partner with ML engineers to ensure smooth integration of feature engineering workflows into ML production systems.
• →Build systems that support agentic ML workflows, including automated feature discovery, feature quality evaluation and feature lifecycle management
• →Drive architecture and technical direction for high-scale ML platform infrastructure powering ads ranking, targeting, and optimization systems.
• →Contribute to operational excellence through observability, performance tuning, reliability engineering, and cost optimization initiatives.
  
  

• 5+ years in infrastructure/platform engineering or large-scale distributed systems.
• 2+ years of hands-on experience building or operating ML platform infrastructure and production ML systems
• Proficiency with large-scale feature computation frameworks (Spark, PySpark, or Scala).
• Expertise in distributed systems (scaling, partitioning, fault tolerance, caching).
• Experience building intelligent automation or agentic workflows for ML systems is a strong plus, including areas such as automated pipeline management, feature recommendations, evaluation systems, or AI-assisted developer tooling.
• Experience with ML infrastructure and MLOps workflows spanning feature engineering, training pipelines, experimentation, model deployment, and online serving is a plus

This job posting may span more than one career level.

In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.