Principal ML Engineer - AI Research (Remote)

Job Description

Posted on: 
October 23, 2023

You'll be part of a team of globally-distributed AI engineers and researchers, focused on bringing the most recent advances in machine learning technology to help our customers efficiently discover and defeat threats. You will collaborate across multiple engineering teams to design and build net new capabilities that will be used across SentinelOne’s industry-leading platform.


  • Provide technical Leadership and Guidance: establishing research and coding standards, system design principles, and best practices; guiding the group in overcoming technical challenges while ensuring that our codebase remains efficient and maintainable
  • Drive Solution Architecture and Design: designing research programs and software systems that meet the requirements of a diverse stakeholder group; planning implementation in a way
  • Perform Hands-On Coding and Code Review
  • Lead Collaboration and communication: collaborating closely with other group members and stakeholders including project managers, product owners, and other engineering teams; ensuring that technical options and decisions, and project timelines, are clearly communicated to all stakeholders
  • Model Continuous Learning and Skill Development: helping the group and the broader team to stay up-to-date with the latest tools and techniques in both the machine learning and security fields; fostering a culture of continuous learning and skill development; mentoring more junior colleagues

Job Requirements

  • 10+ years of experience solving complex problems using modern AI/ML techniques
  • Complete mastery of a subset of the languages, frameworks and tools currently used in the development of data intensive, machine learning systems, e.g. Spark, Airflow, Python, TensorFlow/PyTorch
  • Experience in designing, training, and evaluating models
  • Master’s Degree in any quantitative science or engineering field. Additional or directly relevant experience will be considered in lieu of a degree
  • Experience with the full system development lifecycle, from requirement gathering, research, design, implementation, testing, through deployment/launch and operation
  • Comfort-level working cross-functionally across both research and product teams

Nice to Haves:

  • Postgraduate or advanced degree in a relevant research domain
  • First-author publications at peer-reviewed AI conferences
  • Experience with model parallelism for working with large neural network architectures
  • Expertise in natural language processing, especially practical experience developing modern, transformer-based language models
  • Experience developing complex applications leveraging API-based LLMs
  • Representation learning, especially for temporal sequences
  • Open-source foundation models like T5, Bloom, etc.
  • Multimodal models and systems
  • Lifelong learning systems driven by implicit and explicit product feedback
  • Practical reinforcement learning techniques
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