Poolside

Poolside

Member of Engineering (Synthetic Data Research)

Remote (US)

Sponsorship not specifiedDetected 174 days ago
PythonMachine LearningDeep LearningData EngineeringLLMsAgentic AICadenceResearchCollaboration

About the role

  • You'll be working on our data team focused on the quality of the datasets being delivered for training our models.
  • This is a hands-on role where your #1 mission would be to improve the quality of our datasets across the entire training cycle (pre-training, mid-training, post-training, RL) by leveraging your previous experience, intuition and training experiments.
  • This role particularly focuses on generating synthetic data at scale and determining the best strategies to leverage such data into training large models.

Responsibilities

  • Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.
  • Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.

Requirements

  • Their ability to stack advantages and pull ahead will define the winners.
  • Experience with Large Language Models (LLM), including:
  • Experience with implementing cost-efficient, complex pipelines to generate synthetical datasets at scale optimizing for data quality, correctness, diversity, etc.

Nice to have

  • Can freely discuss the latest papers and descend to fine details
  • Is reasonably opinionated
  • Intro call with one of our Founding Engineers
  • Technical Interview(s) with one of our Members of Engineering
  • Team fit call with the People team
  • Final interview with one of our Founding Engineers
  • Company-provided equipment
  • Frequent team get togethers

Skills

  • Strong machine learning and engineering background
  • Understanding of how LLMs learn
  • Data ablations and scaling laws
  • Post-training techniques
  • Training reasoning and agentic models
  • Experience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)
  • Excellent programming skills in Python
  • Strong prompt engineering skills
  • Experience working with large-scale GPU clusters and distributed data pipelines
  • Strong obsession with data quality

Benefits

  • 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
  • Fully remote work & flexible hours

Company info

  • 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.
  • 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 in Paris each month for 3 days, with an open invitation to stay the whole week.
  • For those based in PST, we understand this is a significant travel cadence; we are open to agree on a lower cadence and will discuss this in the interview process.
  • 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.
  • You'll closely collaborate with other teams like Pre-training, Pre-training data, Post-training, RL2L, Evals, and Product to define high-quality data needs that map to missing model capabilities and downstream use cases.
  • Staying in sync with the latest state-of-the-art research in synthetic data generation and LLM training is key to success in this role.
  • You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly technical engineering solutions into production.
  • With the volumes of data to process being massive, you'll have a performant distributed data pipeline together with large GPU clusters at your disposal.
  • Curious about the tech?
  • Take a deep dive into our data work in our Laguna M.1/XS.2 Technical Report. https://arxiv.org/abs/2605.27605
  • To deliver large, high-quality, and diverse synthetic datasets mixing natural language and code modalities to train best-in-class Poolside coding agents.
  • Follow the latest research related to LLMs and synthetic data generation in particular. Be familiar with the most relevant open-source datasets and models.
  • Closely with cross-team to ensure the experiments run and data generated is the most efficient use of compute and time resources for the improvements in quality of our models.
  • Continuously measure and refine the quality of the datasets being generated while validating the final data strategy through quantitative data ablation experiments.
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