Senior Staff Machine Learning Systems Engineer, Ads ML Platform

🕒 August 25

🇺🇸 United States – Remote

💵 $292.5k - $409.5k / year

⏰ Full Time

🟠 Senior

⚙️ Systems Engineer

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Reddit, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2005

💼 Consulting

📣 Marketing

📱 Media

Consulting • Marketing • Media

Reddit, Inc. is a social media platform that acts as a hub for thousands of communities, where users can engage in diverse conversations ranging from breaking news to niche interests. It enables users to post, comment, and vote on content, fostering a vibrant online community. Millions of people globally connect and share their passions on Reddit, creating a dynamic environment for authentic human interaction.

📋 Description

• Own the technical strategy for the end-to-end Ads ML engineer lifecycle, beginning with feature development, training data, offline experimentation, and model iteration workflows • Align Ads ML platform priorities with Reddit’s broader ML Platform vision • Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency • Identify high-leverage friction points and improve ML engineers’ day-to-day development velocity • Build platform abstractions and workflow automation for faster, safer, more reliable, self-service ML development • Extend the platform strategy into serving and online experimentation workflows • Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams • Mentor Staff and senior engineers, raise the architecture and operational bar, and grow technical leaders

🎯 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 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 technologies • Ability to balance urgent customer needs with durable long-term architecture and reusable platform patterns • Ability to influence senior engineers and leaders through technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms • Excitement about shaping how production ML systems are built, scaled, and operated

🏖️ 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 • Equity in the form of restricted stock units • Medical, dental, and vision insurance • Generous time off for vacation and parental leave