Senior Machine Learning Engineer, Ads Training Platform

Requirements

• 5+ 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.

What You'll Be Doing

• 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.

Nice to Haves

• Experience with deep learning frameworks (PyTorch, TensorFlow) is a big plus.
• Bonus: model optimization for distributed training, Ads ML experience.

Perks and Benefits

• Pension Scheme
• Private Medical and Dental Scheme
• Life Assurance, Income Protection
• Workspace benefit for your home office
• Personal & Professional development funds
• Family Planning Support
• Commuter Benefits
• Flexible Vacation & Reddit Global Days Off