Senior Staff Machine Learning Systems Engineer, Ads ML Platform

Fdetimes; United States; Remote; USD 293,000 - 410,000; Full time

Benefits offered by this job

Healthcare Benefits

401k with Employer Match

Global Benefit programs

Family Planning Support

Gender-Affirming Care

Mental Health & Coaching Benefits

Flexible Vacation

Parental Leave

Job summary

Reddit is seeking a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the Ads ML engineer lifecycle. You will shape feature development, data training loops, and experiments, driving faster delivery and robust production-ready ML systems.

You’ll collaborate with Ads, ML Platform, Data Platform, and engineering teams to define standards and scale the platform, with mentoring responsibilities for senior engineers. This is a senior, impact-driven role.

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, or large 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, or distributed data infra.
• Experience with Spark, Flink, Kafka, Ray, Airflow, Kubernetes, BigQuery, Snowflake, Databricks or similar.

Responsibilities

• Own the technical strategy for the end-to-end Ads ML engineer lifecycle from feature development to model iteration.
• Align Ads ML platform priorities with Reddit’s broader ML Platform vision.
• Define architecture and standards for ML feature and training-data systems across batch/streaming work.
• Stay close to ML engineers to identify friction points and improve development velocity.
• Build platform abstractions and workflow automation for faster, safer ML development.
• Extend strategy into serving and online experimentation workflows for offline-to-online impact.
• Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to drive durable execution.
• Mentor Staff and senior engineers, raising architecture and operational bar.

Skills

Infrastructure

Distributed systems

ML platforms

Leadership

Cross-team collaboration

Feature platforms

Tools

Spark

Flink

Kafka

Ray

Airflow

Kubernetes

BigQuery

Snowflake

Databricks

Job description

Reddit is a community of communities. It’s 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, distributed systems, ML platforms, data platforms, or large-scale backend systems.
• You have 4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.
• You have led broad, ambiguous, multi-team platform initiatives from strategy through adoption.
• You have built platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.
• You have deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.
• You have worked with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.
• You can balance urgent customer needs with durable long-term architecture and reusable platform patterns.
• You influence senior engineers and leaders through clear technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms.
• You are excited to shape how production ML systems are built, scaled, and operated, not only how models are trained.

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

Pay Transparency

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.

The base salary range for this position is

$292,500—$409,500 USD

In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.

During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.

Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.