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Member of Engineering (Post-training)

Role overview

Qualifications

  • Experience with Large Language Models (LLM)
  • Strong deep learning fundamentals
  • Good taste in data
  • Post-training experience with LLMs

Responsibilities

  • Research and experiment on ways to specialize foundational models to agentic use cases
  • Build and maintain data and training pipelines
  • Keep up with latest research, and be familiar with state of the art in LLMs, alignment, synthetic data generation, code generation
  • Design, analyze, and iterate on training/fine-tuning/data generation experiments

Key facts

  • Remote from: EMEA
  • Full time
  • English

Other skills

  • Critical Thinking
  • Collaboration
  • Communication

About the company

poolside logo

poolside

Developer Tools & DevOps Platforms

Company details

Company typeStartup
IndustryDeveloper Tools & DevOps Platforms

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Job description

ABOUT POOLSIDE

In this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.

Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.

ABOUT OUR TEAM

We were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration (and croissants) in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.

Our team is a multidisciplinary blend of research, engineering, and business experts. What unites us is our deep care for what we build together. We’re in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we’ve assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has. By building collaboratively and with intention, we create a compounding effect that moves the entire company forward towards our mission: reaching AGI through intelligence systems built for software development.

ABOUT THE ROLE

You would be working as part of our Applied Research team, focused on turning pre-trained LLMs into well-aligned and highly capable AI systems for coding and software development. This is a hands-on role where you'll work across a variety of efforts, including: Building data pipelines and environments for agentic use cases, researching and implementing post-training algorithms, designing experiments and testing hypothesis, and more. You will have access to thousands of GPUs in this team.

YOUR MISSION

To turn pre-trained LLMs into well-aligned and highly capable AI systems.

RESPONSIBILITIES

  • Research and experiment on ways to specialize foundational models to agentic use cases

  • Build and maintain data and training pipelines

  • Keep up with latest research, and be familiar with state of the art in LLMs, alignment, synthetic data generation, code generation

  • Design, analyze, and iterate on training/fine-tuning/data generation experiments

  • Write high-quality, pragmatic code

  • Work as part of a team: plan future steps, discuss, and communicate clearly with your peers

SKILLS & EXPERIENCE

  • Experience with Large Language Models (LLM)

    • Deep knowledge of Transformers

    • Strong deep learning fundamentals

    • Good taste in data

    • Post-training experience with LLMs

    • Extensively used and probed LLMs, familiarity of their capabilities and limitations

    • Knowledge of distributed training

  • Strong machine learning and engineering background

  • Research experience

    • Experience in proposing and evaluating novel research ideas

    • Familiar with, or contributed to the state of the art in multiple of the following topics: Fine-tuning and alignment of LLMs, synthetic data generation, continual learning, RLVR, code generation

    • Is comfortable in a rapidly iterating environment

    • Is reasonably opinionated

  • Programming experience

    • Linux

    • Strong algorithmic skills

    • Python with PyTorch or Jax

    • Use modern tools, including latest code agents and are always looking to improve

    • Strong critical thinking and ability to question code quality policies when applicable

    • Prior experience in non-ML programming, especially not in Python - is a nice to have

PROCESS

  • Intro call with one of our Founding Engineers

  • Technical Interview(s) with one of our Founding Engineers

  • Team fit call with the People team

  • Final interview with one of our Founding Engineers

BENEFITS

  • Fully remote work & flexible hours

  • 37 days/year of vacation & holidays

  • Health insurance allowance for you & dependents

  • 16 weeks of flexible, full-pay parental leave

  • Well-being, always-be-learning & home office allowances

  • Company-provided equipment

  • Frequent team get togethers

  • Diverse & inclusive people-first culture

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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