Research Engineer/Scientist, Training Algorithms

As a research engineer or research scientist, you will work closely with the rest of the team on cutting-edge deep learning research projects. You will design, develop, test, deploy, maintain and improve the software necessary to accomplish large-scale empirical deep learning research. Additionally, you will generate hypotheses, run experiments, and communicate research results. Finally, you will help other teams adopt the most useful insights and methods the team produces.

Key responsibilities:

• Develop and maintain deep learning research infrastructure to run large scale neural network experiments
• Implement deep learning models and training algorithms using JAX and Flax
• Train deep neural networks to achieve record-breaking results on production and academic datasets
• Conduct careful and rigorous deep learning research projects within the context of the team's research agenda, and communicate the results in technical reports and presentations
• Propose new methods and research projects that align with the team's research agenda of understanding and improving the practice of deep learning

• MSc or PhD in machine learning or a related field, or equivalent industry experience.
• Strong software engineering skills and extensive experience using at least one deep learning framework, such as JAX or PyTorch.
• Track record of releases, publications, and/or open source projects in deep learning

• Experience using JAX specifically, since it is the deep learning framework the team uses
• Research experience and accomplishments (e.g. software artifacts, scientific publications, etc,) in neural network training dynamics, training algorithms and optimizers, training recipes, or hyperparameter tuning

The US base salary range for this full-time position is between $188,000 - $230,000+ bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.