Senior Staff Machine Learning Systems Engineer, Ads ML Platform

EngineersOfAI; Northern (KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Reddit seeks a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle, focusing on feature development, training data, and offline experimentation. The role will drive platform abstractions, automation, and cross-team alignment to accelerate ML product delivery.

You will mentor staff engineers, shape architectural decisions, and partner with Ads, ML Platform, Data Platform, and product teams to deliver durable, scalable ML

Qualifications

• 8+ years of experience in infrastructure or related engineering roles.

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.
• Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.
• Mentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders.

Skills

infrastructure

Job description

Reddit is a community of communities. It is built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Reddit has a flexible workforce! If you happen to live close to one of our physical office locations 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 in any country in which we have a physical presence

About Reddit

Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visit redditinc.com.

Team Overview

The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably.

We are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be 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, this scope will expand into serving and online experimentation workflows, creating a more seamless path from offline iteration to production impact.

This is a senior technical leadership role for someone who can combine deep systems expertise, production ML experience, architectural judgment, and cross-team influence.

What You’ll Do

• 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.

Who You Might Be

• You have 8+ years of experience in infrastructure, dis