Principal ML Engineer, Machine Learning Platform and Systems Architecture

Role Overview

The Principal ML Engineer will lead the design and evolution of large-scale machine learning platforms, working closely with researchers, product teams, and engineering leadership to build systems that bring advanced machine learning into reliable, scalable product experiences.

What You Will Do

Lead architecture and delivery for major ML platform capabilities, design scalable systems for distributed training, data processing, and model lifecycle management, and drive the design and scaling of data pipelines for large-scale structured and semi-structured technical datasets.

Why It Might Be a Fit

The ideal candidate is a strong architect and hands-on engineer who drives clarity and momentum in ambiguous spaces, thinks at platform level, and acts with strong product and business awareness.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience
• Typically 6 to 8 years of industry experience in software engineering, ML infrastructure, distributed systems, or platform engineering
• Deep experience in software architecture, distributed systems, large-scale data platforms, or ML infrastructure
• Strong proficiency in Python and strong command of production software engineering practices
• Experience leading complex technical initiatives that span multiple engineers or cross-functional teams

Benefits

• Health and financial benefits
• Time away
• Everyday wellness
• Annual cash bonuses
• Commissions for sales roles
• Stock grants
• Comprehensive benefits package