Machine Learning Engineer, Ads Training Platform

<h3>📋 Description</h3> • Design, build, and maintain large-scale distributed training infrastructure for Ads ML models. • Develop tools and frameworks on top of the Ray platform. • Build tools to debug, profile, and tune distributed training jobs for performance and reliability. • Integrate with object storage systems and improve data access patterns. • Collaborate with ML engineers to improve model training time, efficiency, and GPU training costs. • Drive improvements in scheduling, state management, and fault tolerance within the training platform to enhance overall performance. <h3>🎯 Requirements</h3> • 3+ years in infrastructure/platform engineering or large-scale distributed systems. • 2+ years hands-on experience with Ray platform. • Strong understanding of distributed computing principles (task scheduling, fault tolerance, state management). • Experience with distributed storage systems and large-scale data processing. • Proven ability to debug and profile distributed jobs. • Experience with deep learning frameworks (PyTorch, TensorFlow) is a big plus. • Bonus: model optimization for distributed training, Ads ML experience. <h3>🏖️ Benefits</h3> • Comprehensive Healthcare Benefits and Income Replacement Programs • 401k Match • Family Planning Support • Gender-Affirming Care • Mental Health & Coaching Benefits • Flexible Vacation & Reddit Global Days off • Generous paid Parental Leave • Paid Volunteer time off