# Senior Staff Machine Learning Systems Engineer, Ads ML Platform

**Company**: Reddit
**Location**: Remote - United States
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: $292,500-$409,500 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/reddit/jobs/8157275?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_21529588-114

## Description

Reddit is seeking a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle.

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.

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.

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 working with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.

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

## Skills

### Required
- ML platforms
- distributed systems
- infrastructure
- data platforms
- large-scale backend systems
- Spark
- Flink
- Kafka
- Ray
- Airflow
- Iceberg
- Kubernetes
- BigQuery
- Snowflake
- Databricks

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/reddit/jobs/8157275?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)