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Senior Staff Machine Learning Systems Engineer, Ads ML Platform

RedditRemote - United StatesAds Engineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Posted
25 Aug 2026
Status
Open · checked 7d ago

About this role

Reddit is seeking a remote Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle across the United States. This senior technical leadership role suits an expert in distributed systems and machine learning infrastructure who wants to drive high-scale platform architecture and developer velocity.

Role Overview

As a Senior Staff Machine Learning Systems Engineer on the Ads ML Platform team, the primary focus centers on the feature development and training iteration loop. Responsibilities include making feature creation faster, generating reliable training data, running offline experiments, and streamlining the path from an idea to a validated model improvement. Over time, the scope will expand into serving and online experimentation workflows to create a seamless offline-to-online machine learning development experience. This position combines deep systems expertise, architectural judgment, and cross-team influence to elevate production machine learning infrastructure.

Key Responsibilities

Own the technical strategy for the end-to-end Ads ML engineer lifecycle, encompassing feature development, training data, offline experimentation, and model iteration workflows.
Align Ads ML platform priorities with the broader Reddit machine learning platform vision, translating specific pain points into reusable capabilities.
Define architecture and technical standards for machine learning feature and training-data systems involving batch and streaming computation, backfills, lineage, quality, observability, and online-offline consistency.
Build platform abstractions and workflow automation to make development faster, safer, more reliable, and self-service.
Extend platform strategy into serving and online experimentation workflows over time.
Partner across ads, machine learning platform, data platform, modeling, product, and engineering teams to clarify ownership and drive durable execution.
Mentor Staff and senior engineers, raise the operational and architectural bar, and help grow upcoming technical leaders.

Requirements

Minimum of 8 years of experience working in infrastructure, distributed systems, machine learning platforms, data platforms, or large-scale backend systems.
At least 4 years of experience building or operating production machine learning infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.
Demonstrated success leading broad, ambiguous, multi-team platform initiatives from initial strategy through adoption.
Experience building platforms used directly by machine learning engineers, data scientists, or product teams developing production machine learning systems.
Proven ability to balance urgent customer needs with durable, long-term architecture and reusable platform patterns.
Skill in influencing senior engineers and leaders through clear technical reasoning, RFCs, design reviews, and decision frameworks.

Skills and Tools

Distributed data and compute technologies including Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, and Databricks.
Machine learning feature platforms, training data pipelines, and online-offline consistency frameworks.
Developer infrastructure, workflow automation, and distributed systems architecture.

Salary and Benefits

Base salary range of $292,500 to $409,500 USD, with final offers determined by skills, depth of work experience, and relevant credentials.
Eligibility to receive equity in the form of restricted stock units.
Comprehensive healthcare benefits and income replacement programs, including medical, dental, and vision insurance.
401(k) program with employer match.
Global benefit programs covering workspace, professional development, and caregiving support, alongside family planning support and gender-affirming care.
Mental health and coaching benefits.
Flexible vacation, paid volunteer time off, and generous paid parental leave.

About the Company

Reddit operates as a community of communities built on shared interests, passion, and trust, housing over 100,000 active communities and approximately 130 million daily active unique visitors. As one of the largest sources of conversation and knowledge on the internet, the company maintains a flexible workforce offering remote work opportunities in countries where physical offices exist.

How to Apply

Apply directly on the official Reddit careers page to submit your application for this remote position.

Skills and tech stack

Questions candidates ask

What is the salary range for the Senior Staff ML Systems Engineer role at Reddit?

The base salary range for this position is $292,500 to $409,500 USD. Additional compensation may include equity in the form of restricted stock units and various company benefits.

Is this position remote?

Yes, this role is remote within the United States, and Reddit supports a flexible workforce across countries where the company has a physical presence.

What experience is required for this role?

Candidates need 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems, including 4+ years building or operating production ML infrastructure, feature platforms, or data pipelines.

What technologies and tools will I work with?

The role involves working with distributed data and compute systems such as Kubernetes, Spark, Kafka, Airflow, Snowflake, Flink, Ray, Iceberg, Databricks, and BigQuery.

What are the primary responsibilities of the Ads ML Platform team?

The team builds infrastructure that accelerates high-scale machine learning systems and tooling for ads, covering the full development lifecycle from feature creation and training data generation to offline experimentation and model deployment.

Ready to apply?

The application is on the official Reddit careers page.

Apply on company site