Llm Training Researcher

2 weeks ago

Toronto, Ontario, Canada Bloomberg Full time

Who we are:

Overview:

We believe that large language models (LLMs) will play a very important role at Bloomberg for the foreseeable future. As an LLM Training Researcher, you will be our resident expert on cutting-edge training strategies for LLMs. Specifically, your focus will be on optimization (e.g. training stability, optimizer choice, learning rates, regularization, batching, float representations), details of architecture choice and objective functions, data-preprocessing (e.g. tokenization and de-duplication strategies), and anything else that would have a material impact on model performance.

You will lead our research into these areas, and you will collaborate with our talented ML researchers in the Engineering division on building LLMs.

You may also develop and leverage collaborations and partnerships with external service providers, where they can be used to substantially accelerate our progress.


We'll trust you to:

  • Establish and continually refine our internal best practices for LLM training
  • Collaborate with engineers on building stateoftheart LLM models
  • Lead research efforts on LLM training, deliver scientific breakthroughs and share these findings at top conferences and through other publication channels
  • Form strategic partnerships with external providers to accelerate our technological advancement

You'll need to have:

  • 5+ years of experience in an applied research role
  • Ph.
D. or equivalent experience in training LLMs

  • Several publications on LLMs or related technologies (e.g. underlying optimization theory)
  • Excellent communication and collaborative skills
  • Blend of longterm strategic vision with goaldriven tactical focus
  • Engagement with the research community (e.g., conference or workshop service).

Nice to have:

  • Understanding of parallelization strategies for largescale LLM training
Bloomberg is an equal opportunity employer and we value diversity at our company.

We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

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