Poolside19.05.2026

Member of Engineering (Pre-training / Data Research)

Полная занятостьУдалёнка

Обязанности

01Follow the latest research related to LLMs and data quality in particular. Be familiar with the most relevant open-source datasets and models.
02Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.
03Closely work with other teams such as Pretraining, Posttraining, Evals and Product to ensure short feedback loops on the quality of the models delivered.
04Suggest, conduct and analyze data ablations or training experiments that aim to improve the quality of the datasets generated via quantitative insights.

01Strong machine learning and engineering background
02Experience with Large Language Models (LLM)
03Understanding of transformer architectures and how LLMs learn
04Data ablations and scaling laws
05Mid-training and Post-training techniques
06Training reasoning and agentic models
07Experience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)
08Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.
09Excellent programming skills in Python
10Strong prompt engineering skills
11Experience working with large-scale GPU clusters and distributed data pipelines
12Strong obsession with data quality
13Research experience
14Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to have
15Can freely discuss the latest papers and descend to fine details
16Is reasonably opinionated