Deep Learning Engineer

3 weeks ago

palo alto, United States Skidaway Full time

About us

Our mission at Skidaway is to return the initiative to defenders. Our vision is of Collective Defense for Cybersecurity - via deep learning. We believe we are playing a small role in defending our way of life from ever more innovative and organized attackers.   


Role Description

This is a full-time role for a Deep Learning Engineer. The role requires a strong command of machine learning algorithms, especially deep learning, and the ability to apply them to real-world business problems. We build models from the ground up, so a thorough understanding of transformer-based models and similar approaches is critical.  


Expertise in training and inference utilizing multi-GPU clusters is required. Experience in building transformer models for natural language processing is strongly preferred.  


Our approach harnesses the collective for defense; subjects like transfer learning, the ability of our models to generalize, federated learning, and differential privacy are all day-to-day concerns where you will play a leading role.  


You will be joining a small team, so your impact will be enormous. You will be on a journey with a very experienced team of successful entrepreneurs.


The role is almost entirely remote. We gather approximately monthly in Palo Alto as a team.


Qualifications


  • 3+ years of experience in data science, statistics, or a related field
  • Expertise in PyTorch, HuggingFace and related deep-learning packages
  • Experience in transformer-based models 
  • Kaggle and similar competitive experiences are preferred as they show adaptability and speed
  • OpenSource experience helpful
  • Ability to work independently and as part of a cross-functional team
  • Excellent written and verbal communication skills
  • Cyber security experience preferred 
  • Passionate about building impactful technologies and organizations
  • Master's or PhD degree in Computer Science, Statistics, Mathematics, or a related field 

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