Member of Engineering – Reinforcement Learning

🕒 April 28

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

poolside

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2023

🤖 Artificial Intelligence

🏢 Enterprise

Artificial Intelligence • Enterprise

poolside is a frontier AI lab and enterprise platform that builds and deploys foundation models, multi-agent systems, and developer-facing tools focused on automating complex software work. The company specializes in on-prem and VPC deployments, security-first integrations, governance, and connectors to enterprise data sources so organizations can run agents and models inside their own boundaries. Poolside embeds research and engineering with customers to deliver outcome ownership, risk controls, and measurable business impact while advancing toward AGI by starting in high-consequence software environments.

📋 Description

• Research and experiment on ways to improve reasoning and code generation for LLMs. Own the full experiment life cycle from idea to experimentation and integration • Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation. Translate research ideas into clean, reusable codebases that other researchers can build on • Design, analyze, and iterate on data generation and training of LLMs • Implement and iterate on RL training pipelines that scale reliably across domains • Diagnose training instabilities and failures, debug RL runs and propose mitigation methods • Write high-quality, reproducible and maintainable code

🎯 Requirements

• Experience with Large Language Models (LLM), including: • Understanding of the Transformer architecture and scaling laws • Mid-training and post-training techniques • Experience training reasoning and/or agentic models • Hands-on use of LLMs, with a sense of their capabilities and limitations • Reinforcement Learning experience • Solid grasp of Reinforcement Learning concepts and familiarity with modern algorithms • Experience developing distributed, large-scale RL pipelines from data creation to evaluations • Research experience • Scientific publications in any of the following topics: Reinforcement Learning, LLMs and reasoning models • Ability to discuss the latest research with sufficient level of detail • Is reasonably opinionated • Engineering skills • Strong machine learning, algorithm skills and engineering background • Experience with distributed training • Excellent programming skills in Python • Familiarity with a deep learning framework (Pytorch or JAX)

🏖️ 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