Machine Learning Systems Platform Engineer

Confidential Opening : Machine Learning Systems Platform Engineer

Location : San Francisco, CA (Hybrid Preferred)

Overview

A stealth-mode innovator at the forefront of AI infrastructure is seeking a dynamic Machine Learning Systems Platform Engineer to build the backbone of their next-generation ML ecosystem. This team is leading the charge in developing tools and platforms that empower world-class ML teams to experiment, scale, and deploy faster than ever before.

In this key engineering role, you will architect and optimize the systems that make high-performance AI development possible. From training and tuning to inference and monitoring, your work will enable cutting-edge ML initiatives across the organization. You will work closely with ML scientists and engineers to ensure seamless integration of models into production environments.

Key Responsibilities

• Build and maintain robust infrastructure to support machine learning workloads at scale, including training pipelines, tuning environments, and deployment frameworks.
• Develop and automate MLOps pipelines for reproducibility, experiment tracking, model versioning, and validation.
• Optimize cloud and on-prem GPU compute utilization across orchestration platforms.
• Lead the implementation of tools for model rollback, observability, and system health monitoring.
• Collaborate with cross-functional teams to ensure reliability, scalability, and maintainability of ML systems.

Qualifications

Preferred Skills

Compensation and Benefits

Why Apply?

This is a rare opportunity to own and shape the ML platform behind AI that will define the next era. If you thrive in system-level problem solving and want to leave your mark on how machine learning is built at scale, this role is for you.

Apply today to learn more about this confidential opportunity and how you can play a part in the future of AI engineering.

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