Senior Machine Learning Systems Engineer, Ads ML Experience Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop large-scale offline machine learning experimentation platforms that facilitate reproducible research, model development, evaluation, and promotion workflows.

• Construct production-quality training orchestration frameworks that support distributed training, hyperparameter optimization, model evaluation, and automated retraining processes.

• Establish infrastructure for experiment tracking, metadata management, lineage, artifact versioning, model registries, and ensuring reproducibility.

• Collaborate with machine learning engineers and researchers to enhance experimentation velocity and operational efficiency.

• Develop automated workflows for model promotion, rollback processes, compliance validation, and ongoing evaluation.

• Design and implement an agentic AI execution platform that supports both autonomous and human-in-the-loop workflows, including multi-agent orchestration, memory/context systems, and scalable workflow infrastructure.

⛳️ Requirements

• Over 5 years of experience in infrastructure/platform engineering or large-scale distributed systems.

• At least 2 years of practical experience in building and managing production machine learning infrastructure, developer SDKs, platform APIs, or self-service AI tools.

• Proven experience in constructing workflow orchestration systems, developer platforms, or large-scale automation frameworks.

• Experience with distributed data processing systems such as Spark, Flink, Ray, or equivalent technologies.

• Familiarity with modern orchestration and workflow technologies including Kubeflow, Argo, Airflow, or similar frameworks.

• Experience in building offline machine learning experimentation platforms, model registries, experiment tracking systems, or training orchestration frameworks.

• Experience in developing and operating agentic AI systems, including multi-agent orchestration, autonomous workflows, and agent communication/runtime frameworks (e.g., MCP, A2A, and orchestration systems) is highly desirable.

• Experience managing end-to-end model development and iteration cycles at scale is a plus.

🏝️ Benefits

• Medical, dental, and vision insurance.

• 401(k) program with employer match.

• Generous vacation time off.

• Parental leave.