Engineering Member - Pre-training / Data

Yesterday

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Poolside

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Description

•About Poolside: Building AI for valuable work and progress. •Remote-first team across Europe and North America. •Hands-on role in improving pretraining dataset quality. •Collaborate with teams on data quality. •Stay updated with research in dataset design and pretraining. •Deliver high-quality natural language and source code datasets for AI training.

Requirements

•Strong machine learning and engineering background •Experience with Large Language Models (LLM) •Good knowledge of Transformers is a must •Knowledge/Experience with cutting-edge training tricks •Knowledge/Experience of distributed training •Trained LLMs from scratch •Knowledge of deep learning fundamentals •Experience in building trillion-scale pretraining datasets, in particular: •Ingest, filter and deduplicate large amounts of web and code data •Familiar with concepts making SOTA pretraining datasets: multi-linguality, curriculum learning, data augmentation, data packing, etc •Run data ablations, tokenization and data-mixture experiments •Develop prompt engineering pipelines to generate synthetic data at scale •Fine-tuning small models for data filtering purposes •Experience working with large-scale GPU clusters and distributed data pipelines •Strong obsession with data quality •Research experience •Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc, is a nice to have •Can freely discuss the latest papers and descend to fine details •Is reasonably opinionated •Programming experience •Strong algorithmic skills •Linux •Git, Docker, k8s, cloud managed services •Data pipelines and queues •Python with PyTorch or Jax •Nice to have: •Prior experience in non-ML programming, especially not in Python •C/C++, CUDA, Triton

Benefits

•Fully remote work & flexible hours •37 days/year of vacation & holidays •Health insurance allowance for you and dependents •Company-provided equipment •Wellbeing, always-be-learning and home office allowances •Frequent team get togethers •Great diverse & inclusive people-first culture

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