Member of Engineering, Fine-tuning

About poolside

In this decade, the world will create artificial intelligence that reaches human level intelligence (and beyond) by combining learning and search. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will determine who survives and wins. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research and engineering at scale. They will create powerful economic engines. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this.

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 because it's the domain where we can combine Search and Learning approaches the best.

At poolside we believe our applied research needs to culminate in products that are put in the hands of people. Today we focus on building for a developer-led increasingly AI-assisted world. We believe that current capabilities of AI lead to incredible tooling that can assist developers in their day to day work. We also believe that as we increase the capabilities of our models, we increasingly empower anyone in the world to be able to build software. We envision a future where not 100 million people can build software but 2 billion people can.

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About our team

We are a remote-first team that sits across Europe and North America and comes together once a month in-person for 3 days and for longer offsites twice a year.

Our R&D and production teams are a combination of more research and more engineering-oriented profiles, however, everyone deeply cares about the quality of the systems we build and has a strong underlying knowledge of software development. We believe that good engineering leads to faster development iterations, which allows us to compound our efforts.

About the role

You would be working as part of our Applied Research team, focused on turning pre-trained LLMs into well-aligned and highly capable AI systems for coding and software development. This is a hands-on role where you'll work across a variety of efforts, including: Building data pipelines for coding use cases, researching and implementing fine-tuning algorithms, training reward models, and more. You will have access to thousands of GPUs in this team.

Your mission

To turn pre-trained LLMs into well-aligned and highly capable AI systems.

Responsibilities

• Research and experiment on ways to specialize foundational models to coding use cases
• Build and maintain data and training pipelines
• Keep up with latest research, and be familiar with state of the art in LLMs, alignment, synthetic data generation, 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 your peers

Skills & Experience

• Experience with Large Language Models (LLM)
• Deep knowledge of Transformers
• Strong deep learning fundamentals
• Good taste in data
• Fine-tuning experience with LLMs
• Extensively used and probed LLMs, familiarity of their capabilities and limitations
• Knowledge of distributed training
• Strong machine learning and engineering background
• Research experience
• Experience in proposing and evaluating novel research ideas
• Familiar with, or contributed to the state of the art in multiple of the following topics: Fine-tuning and alignment of LLMs, synthetic data generation, continual learning, RLHF, code generation
• Is comfortable in a rapidly iterating environment
• Is reasonably opinionated
• Programming experience
• Linux
• Strong algorithmic skills
• Python with PyTorch or Jax
• Use modern tools and are always looking to improve
• Strong critical thinking and ability to question code quality policies when applicable
• Prior experience in non-ML programming, especially not in Python - is a nice to have

Process

• Intro call with one of our Founding Engineers
• Technical Interview(s) with one of our Founding Engineers
• Team-fit call with Beatriz, our Head of People
• Final interview with Eiso, our CTO & Co-Founder

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