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Senior Staff Machine Learning Systems Engineer, Ads ML Platform

Reddit· Ads Product & Engineering
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Remote$292.5k - $409.5kfull-timePosted 2mo ago

About the role

Senior technical leadership role to define and execute the end-to-end Ads ML engineer lifecycle within Reddit’s Ads ML Platform, focusing initially on feature development and training iteration loops, with expansion into serving and online experimentation workflows.

Responsibilities

  • 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 where appropriate.
  • Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.
  • Stay close to ML engineers and platform customers to identify high-leverage friction points and improve day-to-day development velocity.
  • Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service.
  • Over time, extend the platform strategy into serving and online experimentation workflows, creating a more seamless offline-to-online ML development experience.
  • Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership, resolve ambiguity, and drive durable execution.
  • Mentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders.

Qualifications

  • 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.
  • Led broad, ambiguous, multi-team platform initiatives from strategy through adoption.
  • Built platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.
  • Deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.
  • Worked with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.
  • Ability to balance urgent customer needs with durable long-term architecture and reusable platform patterns.
  • Influences senior engineers and leaders through clear technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms.
  • Excited to shape how production ML systems are built, scaled, and operated, not only how models are trained.]

Skills

Required:ML platform developmentdistributed systemsleadership and stakeholder management

Benefits

  • Comprehensive Healthcare Benefits and Income Replacement Programs
  • 401k with Employer Match
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • Family Planning Support
  • Gender-Affirming Care
  • Mental Health & Coaching Benefits
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave
Last updated Oct 7, 2026. Interested? Apply on the company site.
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