Compensation Overview

Company Description:

Founded in late 2020 by a small group of machine learning engineers and researchers, MosaicML enables companies to securely fine-tune, train and deploy custom AI models on their own data, for maximum security and control. Compatible with all major cloud providers, the MosaicML platform provides maximum flexibility for AI development. Introduced in 2023, MosaicML’s pretrained transformer models have established a new standard for open source, commercially usable LLMs and have been downloaded over 3 million times. MosaicML is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Now part of Databricks since July 2023, we are passionate about enabling our customers to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI platform so our customers can use deep data insights to improve their business. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.

Job description:

You will work with one or more researchers on a project that will advance our existing projects toward making neural network training more efficient. This may include:

• Adapting, improving, and evaluating a method from the literature.
• Designing an entirely new method.
• Composing together multiple methods to create new recipes for efficient training.
• Scientifically investigating how neural networks learn in practice.
• Exploring new approaches for training neural networks.

Your qualifications and qualities:

•  Required:
• Pursuing an undergraduate or graduate degree in computer science or related fields (electrical engineering, neuroscience, physics, math, etc.).
• Some proficiency with the fundamentals of deep learning.
• Proficient software engineering skills, including with PyTorch.
• Nice to have:
  
  
• Knowledge of the systems aspects of how neural networks train and the resources utilized in the process of doing so.
• Research experience in deep learning.