About The Position

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will interact closely with our customers and with the academic and research communities. The AGI team has a mission to push the envelope in GenAI with Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.

Requirements

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • 1+ years of building models for business application experience
  • Experience programming in Java, C++, Python or related language
  • Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF

Nice To Haves

  • PhD in Computer Science, Electrical Engineering, Mathematics or related field
  • Strong experience with Generative Artificial Intelligence (GenAI) technologies and Large Language Models (LLMs)
  • Experience with patents or publications at top-tier peer-reviewed conferences or journals
  • Experience with popular deep learning frameworks, including PyTorch

Responsibilities

  • Join us to work as an integral part of a team that has experience with GenAI models in this space.
  • We work on these areas: - Scaling laws - Hardware-informed efficient model architecture, low-precision training - Optimization methods, learning objectives, curriculum design - Deep learning theories on efficient hyperparameter search and self-supervised learning - Learning objectives and reinforcement learning methods - Distributed training methods and solutions - AI-assisted research

Benefits

  • health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
  • 401(k) matching
  • paid time off
  • parental leave
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