Member of Engineering (Post-training) - Poolside

About Poolside

Poolside exists to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.

About Our Team

We were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.

Our team is a multidisciplinary blend of research, engineering, and business experts. We’re in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we’ve assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has.

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 and environments for agentic use cases, researching and implementing post-training algorithms, designing experiments, and testing hypotheses with access to thousands of GPUs.

Responsibilities

• Research and experiment on ways to specialize foundational models to agentic 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

• Large Language Models (LLM): Deep knowledge of Transformers, strong deep learning fundamentals, good taste in data, post-training experience, extensive usage/probing of LLMs, and knowledge of distributed training.
• Machine Learning & Research: Experience in proposing and evaluating novel research ideas. Familiar with or contributed to state-of-the-art topics like fine-tuning, alignment, synthetic data generation, continual learning, RLVR, and code generation.
• Programming: Strong Linux and algorithmic skills, Python with PyTorch or Jax, experience with modern tooling and code agents.

Benefits

• Fully remote work & flexible hours
• 37 days/year of vacation & holidays
• Health insurance allowance for you & dependents
• 16 weeks of flexible, full-pay parental leave
• Well-being, always-be-learning & home office allowances
• Company-provided equipment
• Frequent team get-togethers