Senior Machine Learning Engineer - Ads Training Platform
Reddit has a flexible first workforce! if you happen to live close to our physical office location our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the Netherlands or the United Kingdom.
Team Overview The Ads Training Platform pod builds and maintains the distributed training and data processing infrastructure that powers Reddit’s Ads machine learning models. We focus on enabling fast, reliable, and scalable model training across large datasets, supporting the Ads ML teams in improving ad targeting, conversion prediction, and advertiser value.
We are looking for an engineer with deep experience in infrastructure, distributed systems, and ML platform operations to help evolve and scale our training systems.
What You’ll Do
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.
What You Bring
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.
Experience with deep learning frameworks (PyTorch, TensorFlow) is a big plus.
Bonus: model optimization for distributed training, Ads ML experience.
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
Senior Machine Learning Engineer - Ads Training Platform
Reddit has a flexible first workforce! if you happen to live close to our physical office location our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely from the Netherlands or the United Kingdom.
Team Overview The Ads Training Platform pod builds and maintains the distributed training and data processing infrastructure that powers Reddit’s Ads machine learning models. We focus on enabling fast, reliable, and scalable model training across large datasets, supporting the Ads ML teams in improving ad targeting, conversion prediction, and advertiser value.
We are looking for an engineer with deep experience in infrastructure, distributed systems, and ML platform operations to help evolve and scale our training systems.
What You’ll Do
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.
What You Bring
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.
Experience with deep learning frameworks (PyTorch, TensorFlow) is a big plus.
Bonus: model optimization for distributed training, Ads ML experience.
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