Member of Engineering (Post-training)

Responsibilities

• ▹Research and experiment on ways to specialize foundational models for agentic use cases
• ▹Build and maintain data and training pipelines
• ▹Keep up with the latest research in LLMs, alignment, synthetic data generation, and 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 peers

Requirements

• ▹Experience with Large Language Models (LLMs)
• ▹Deep knowledge of Transformers
• ▹Strong deep learning fundamentals
• ▹Good taste in data
• ▹Post-training experience with LLMs
• ▹Extensive hands-on use of LLMs, familiarity with their capabilities and limitations
• ▹Knowledge of distributed training
• ▹Strong machine learning and engineering background
• ▹Research experience
• ▹Experience proposing and evaluating novel research ideas
• ▹Programming experience, Linux, strong algorithmic skills, Python with PyTorch or Jax

Nice to have

• ▹Familiarity with or contributions to the state of the art in: fine-tuning and alignment of LLMs, synthetic data generation, continual learning, RLVR, code generation
• ▹Comfortable in a rapidly iterating environment
• ▹Reasonably opinionated
• ▹Uses modern tools, including the latest code agents

Soft skills

What we offer

• ▹Monthly 3-day (Monday–Wednesday) in-person team gathering in Paris, with an open invitation to stay the full week
• ▹Annual longer team off-sites

About the company

Poolside exists to build a world where AI is the engine behind economically valuable work and scientific progress. The company believes the fastest path to AGI is accelerating software development itself through agentic systems, coding assistants, and frontier models deployed into the development environments of security-conscious enterprises. Founded in the US, the team is distributed across Europe and North America and gathers in person in Paris each month.