Software Engineer 5, Training Platform, AI Platform

What you'll do

• Design and build the platform for large-scale machine learning model training, fine-tuning, and evaluation workflows.
• Optimize systems and models to increase the cost-effectiveness and scalability of distributed training jobs.
• Develop easy-to-use APIs and interfaces for ML practitioners and non-experts to access the training platform.
• Diagnose and optimize performance metrics including GPU utilization, memory efficiency, and communication overhead.
• Build and operate platform infrastructure, libraries, and SDKs for foundation models and generative AI.
• Implement best practices for observability, logging, reporting, and on-call processes to ensure engineering excellence.
• Lead technical design reviews and facilitate cross-functional discussions to align stakeholders on platform direction.

What we're looking for

• Design, build, and operate platform infrastructure, libraries, and SDKs for large-scale model training.
• Enable reliable and efficient training workflows for foundation models and generative AI models of all sizes.
• Diagnose and optimize performance of large distributed training jobs, including GPU utilization, memory efficiency, and fault tolerance.
• Experience with cloud computing providers, preferably AWS (preferred).
• Ability to work across multiple layers of the tech stack to execute on both 0-to-1 and 1-to-100 projects.
• Adopt and promote best practices in operations, including observability, logging, reporting, and on-call processes.
• Excellent written and verbal communication skills.
• Experience with large-scale distributed training and parallelism techniques such as FSDP and tensor/pipeline parallelism (preferred).