Tech Lead for Distributed ML Systems & Training Platform

Scale AI; New York, San Francisco (NY, CA); On-site; USD 275,000 - 350,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Retirement benefits

Learning and development stipend

Generous PTO

Commuter stipend

Job summary

A leading AI technology firm in New York is seeking a talented individual to build and optimize their training and inference frameworks for large language models. The ideal candidate will collaborate with ML teams to accelerate research and development, bringing expertise in multi-node training and large-scale ML systems. This position offers a competitive salary and benefits, making it an exciting opportunity for those passionate about AI innovation.

Qualifications

• Passionate about system optimization.
• Experience with multi-node LLM training and inference.
• Experience with developing large-scale distributed ML systems.

Responsibilities

• Build, profile, and optimize the training and inference framework.
• Collaborate with ML and research teams.
• Research and integrate state-of-the-art technologies.

Skills

System optimization

Multi-node LLM training and inference

Developing large-scale distributed ML systems

Post-training methods (RLHF/RLVR)

Software engineering skills

Strong communication skills

Tools

CUDA

Pytorch

Transformers

Flash attention

Job description

A leading AI technology firm in New York is seeking a talented individual to build and optimize their training and inference frameworks for large language models. The ideal candidate will collaborate with ML teams to accelerate research and development, bringing expertise in multi-node training and large-scale ML systems. This position offers a competitive salary and benefits, making it an exciting opportunity for those passionate about AI innovation.