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RedditRedditUnited States

Senior Machine Learning Systems Engineer

Build large-scale ML experimentation and training orchestration platforms, including agentic AI execution systems, to accelerate Ads ML development at Reddit. Requires 5+ years infrastructure experience and 2+ years building production ML platforms.

217k – 303k
Remote5+ YOEML Engineering

About the role

What You’ll Do

  • 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.

What You Bring

  • 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.

Skills

SparkFlinkRayKubeflowArgoAirflowMl Experimentation PlatformsModel RegistriesExperiment TrackingTraining OrchestrationAgentic Ai SystemsMulti-Agent Orchestration

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