# Senior Staff Machine Learning Systems Engineer, Ads ML Platform

**Company:** [Reddit](https://hotfix.jobs/companies/reddit)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $293k – $410k/yr
**Experience:** 8+ years
**Skills:** Machine Learning, Ml Platforms, Distributed Systems, Backend Systems, Feature Platforms, Training Data Systems, Offline Experimentation, Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery
**Posted:** 2026-08-25

> Leads technical strategy for Reddit’s Ads ML Platform, improving feature development, training-data generation, experimentation, and the path to production ML serving. The role requires 8+ years in infrastructure or distributed systems, production ML platform experience, and strong cross-team technical leadership.

## Job Description

## Responsibilities
- 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 and translate Ads needs into reusable platform capabilities.
- Define architecture and technical standards for ML feature and training-data systems across batch and streaming computation, backfills, lineage, quality, observability, and online/offline consistency.
- Identify high-leverage friction points for ML engineers and improve development velocity.
- Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and self-service.
- Extend platform strategy into serving and online experimentation workflows.
- Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership and drive execution.
- Mentor Staff and senior engineers and raise architecture and operational standards.

## 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 by ML engineers, data scientists, or product teams developing production ML systems.
- Deep experience with ML platforms, feature platforms, training data, experimentation, developer infrastructure, or distributed data infrastructure.
- Ability to balance urgent customer needs with durable architecture and reusable platform patterns.
- Ability to influence senior engineers and leaders through technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms.

## Nice-to-haves
- Experience with distributed data and compute technologies such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, or Databricks.
- Interest in shaping how production ML systems are built, scaled, and operated.

## Compensation & Benefits
- Base salary range: **$292,500–$409,500 USD**.
- Equity in the form of restricted stock units; some positions may also be eligible for commission.
- Comprehensive healthcare benefits and income replacement programs.
- 401(k) with employer match.
- Global benefits supporting workspace, professional development, caregiving, and family planning.
- Gender-affirming care.
- Mental health and coaching benefits.
- Flexible vacation and paid volunteer time off.
- Generous paid parental leave.

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