Senior Machine Learning Systems Engineer, Ads ML Experience Platform

Reddit

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$216,700–$303,400 / yr
Posted
32 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $230k
This role $260k
$170k most similar roles pay here $318k

This role pays more than 78% of similar roles. Most pay $202,800–$256,237 — the shaded band above. At the midpoint, this role pays about $260k versus about $230k for comparable roles.

Based on 240 similar postings.

Employer

About Reddit

Reddit is a social news aggregation and discussion platform where users share content, vote on posts, and engage in community conversations across thousands of interest-based forums called subreddits.

Reddit currently has 77 open roles on FindRole.

Listed pay typically runs $217,000–$303,400 across 77 roles with salary data.

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At a glance

TL;DR · Senior Machine Learning Systems Engineer, Ads ML Experience Platform

Senior Machine Learning Systems Engineer, Ads ML Experience Platform joins the team building next-generation machine learning research tools and agentic AI platforms to accelerate the Ads ML lifecycle. You will design and build large-scale offline experimentation platforms for reproducible research, develop production-grade training orchestration frameworks for distributed training and hyperparameter optimization, and construct infrastructure for experiment tracking, metadata management, and model registries. Additionally, you will build an agentic AI execution platform supporting multi-agent orchestration and memory systems. The role requires expertise in large-scale distributed systems, developer SDKs, and automated workflows. Key technologies include Spark, Flink, Ray, Kubeflow, Argo, and Airflow. You will solve complex problems regarding model promotion, compliance validation, and autonomous operations to improve experimentation velocity and operational efficiency for researchers and engineers within the advertising machine learning domain.

What you'll do

  • Design and build large-scale offline ML experimentation platforms for reproducible research and model development.
  • Develop production-grade training orchestration frameworks supporting distributed training and hyperparameter optimization.
  • Build infrastructure for experiment tracking, metadata management, lineage, and artifact versioning.
  • Create automated workflows for model promotion, rollback, compliance validation, and continuous evaluation.
  • Design and build an agentic AI execution platform supporting multi-agent orchestration and memory systems.
  • Develop scalable workflow infrastructure to support both autonomous and human-in-the-loop processes.

What we're looking for

  • 5+ years of experience in infrastructure/platform engineering or large-scale distributed systems.
  • 2+ years of hands-on experience building and operating production ML infrastructure, developer SDKs, platform APIs, or self-service AI tooling.
  • Experience building workflow orchestration systems, developer platforms, or large-scale automation frameworks.
  • Experience with distributed data processing systems such as Spark, Flink, Ray, or equivalent technologies.
  • Experience with modern orchestration and workflow technologies such as Kubeflow, Argo, Airflow, or similar frameworks.
  • Experience building offline ML experimentation platforms, model registries, experiment tracking systems, or training orchestration frameworks.
  • Experience building and operating agentic AI systems, including multi-agent orchestration and autonomous workflows (preferred).
  • Experience running end-to-end model development and iteration cycles at scale (preferred).

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