Scale AI, Inc.
Tech Lead Manager- MLRE, ML Systems Research New York, NY
Scale AI, Inc., New York, New York, us, 10261
Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline.
Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation.
If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!
You will:
Build, profile and optimize our training and inference framework.
Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
Research and integrate state-of-the-art technologies to optimize our ML system.
Ideally you’d have:
Passionate about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills to operate in a cross functional team environment.
Nice to haves:
Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$275,000 — $350,000 USD
PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
#J-18808-Ljbffr
Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation.
If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!
You will:
Build, profile and optimize our training and inference framework.
Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation.
Research and integrate state-of-the-art technologies to optimize our ML system.
Ideally you’d have:
Passionate about system optimization
Experience with multi-node LLM training and inference
Experience with developing large-scale distributed ML systems
Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc.
Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc.
Strong written and verbal communication skills to operate in a cross functional team environment.
Nice to haves:
Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc.
Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:
$275,000 — $350,000 USD
PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.
#J-18808-Ljbffr