Member of Engineering - Inference

March 7

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Poolside

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Poolside is an accelerator specifically designed for web3 founders and builders. It provides support for projects in decentralized finance, gaming, governance, infrastructure, and NFTs. With a robust ecosystem of 20,000 members, including mentors, investors, and web3 builders, Poolside has co-launched and supported over 110 projects. The accelerator offers unique access to mentorship and technical expertise to help web3 projects scale and achieve successful launches. Poolside also engages with leading companies and protocols to drive growth and innovation in the web3 space.

Blockchain • Accelerator • Incubator • Hub • Fundraising

11 - 50 employees

🌐 Web 3

💳 Fintech

🎮 Gaming

📋 Description

• ABOUT POOLSIDE: In this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search. • poolside exists to be one of these companies - to build a world where AI will drive the majority of economically valuable work and scientific progress. • We believe that software development will be the first major capability in neural networks that reaches human-level intelligence. • At poolside we believe our applied research needs to culminate in products that are put in the hands of people. • We envision a future where not 100 million people can build software but 2 billion people can. • ABOUT OUR TEAM: We are a remote-first team that sits across Europe and North America. • Our R&D and production teams are a combination of more research and more engineering-oriented profiles. • ABOUT THE ROLE: You will be focused on building out our multi-device inference of Large Language Models. • YOUR MISSION: To develop and continuously improve the inference of LLMs for source code generation.

🎯 Requirements

• Experience with Large Language Models (LLM) • Confident knowledge of the computational properties of transformers • Knowledge/Experience with cutting-edge inference tricks • Knowledge/Experience of distributed and lower precision inference • Knowledge of deep learning fundamentals • Strong engineering background • Theoretical computer science knowledge is a must • Experience with programming for hardware accelerators • SIMD algorithms • Expert in matrix multiplication bottlenecks • Know hardware operation latencies by heart • Research experience • Nice to have but not required: Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc • Can freely discuss the latest papers and descend to fine details • You have strong opinions, weakly held • Programming experience • Linux • Git • Python with PyTorch or Jax • C/C++, CUDA, Triton, ThunderKittens • Use modern tools and are always looking to improve • Opinionated but reasonable, practical, and not afraid to ignore best practices • Strong critical thinking and ability to question code quality policies when applicable • Prior experience in non-ML programming is a nice to have

🏖️ 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