Research Engineer/Scientist

📋 Description Own LLM mid-training and post-training research, including continued pretraining, SFT, preference Research and prototype novel agentic architectures and algorithms across planning, reasoning Design and build research harnesses and experimentation methodologies that enable systematic Define evaluation methodologies and develop novel benchmarks for measuring agent reasoning Identify systematic model and agent failure patterns, determine their root causes, and translate Independently identify research problems, formulate novel hypotheses, and drive projects from 🎯 Requirements 3+ years of experience in machine learning, deep learning, AI research, or a related field, with Hands-on experience with LLM training and post-training, including one or more of continued Strong Python and advanced PyTorch expertise, with experience modifying models, training pipelines Strong practical depth in agentic AI and context engineering, including planning, reasoning Experience designing evaluation methodologies, not just running evaluations, including benchmark Demonstrated research ownership and impact, with the ability to identify important research 🎁 Benefits Work personas categorized as flexible, remote, or required in office depending on nature of work Equal opportunity employer Reasonable accommodations for candidates Export control regulations compliance