Senior Machine Learning Systems Engineer, Ads ML Experience Platform

Reddit, Inc. is a community-driven platform that hosts open conversations on the internet, and they are seeking a Senior Machine Learning Systems Engineer to enhance their Ads ML Experience Platform. The role involves designing and building large-scale ML experimentation platforms, developing production-grade training orchestration frameworks, and collaborating with ML engineers to improve operational efficiency.

Responsibilities:

• Design and build large-scale offline ML experimentation platforms that enable reproducible research, model development, evaluation, and promotion workflows
• Develop production-grade training orchestration frameworks supporting distributed training, hyperparameter optimization, model evaluation, and automated retraining
• Build infrastructure for experiment tracking, metadata management, lineage, artifact versioning, model registries, and reproducibility
• Partner with ML engineers and researchers to improve experimentation velocity and operational efficiency
• Build automated workflows for model promotion, rollback, compliance validation, and continuous evaluation
• Design and build an agentic AI execution platform supporting autonomous and human-in-the-loop workflows, including multi-agent orchestration, memory/context systems, and scalable workflow infrastructure

Requirements:

• 5+ years 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, autonomous workflows, and agent communication/runtime frameworks (e.g., MCP, A2A, and orchestration systems) is a strong plus
• Experience running end-to-end model development and iteration cycles at scale is a plus