AI Researcher

CrosbyNew York, NY
2d

About The Position

As an AI Researcher at Crosby, you'll play a critical role in advancing the capabilities of our AI systems. You’ll explore, develop, and apply state-of-the-art techniques in LLMs and applied NLP to improve how our platform understands, analyzes, and reasons over complex legal documents. You’ll work closely with engineers, data scientists, and legal experts to translate research ideas into production systems. This role is for someone who is deeply curious, technically rigorous, and motivated to push the boundaries of what AI can do in high-stakes domains.

Requirements

  • 3–7+ years of experience in AI research, machine learning, or applied NLP
  • Strong foundation in machine learning, deep learning, and statistical methods
  • Hands-on experience working with LLMs, transformers, and modern NLP techniques
  • Experience running experiments and evaluating model performance in a rigorous, structured way
  • Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or similar
  • Strong problem-solving skills and the ability to translate ambiguous challenges into research directions
  • Effective communicator who can collaborate across technical and non-technical teams
  • Curious, driven, and excited about applying research to real-world, high-impact problems

Responsibilities

  • Advance model capabilities: Research and develop novel approaches to improve performance on tasks like document understanding, clause extraction, reasoning, and negotiation.
  • Experiment and iterate: Design and run experiments to evaluate new architectures, prompting strategies, fine-tuning approaches, and retrieval methods.
  • Bridge research and production: Work closely with engineering teams to translate research insights into scalable, production-ready systems.
  • Improve evaluation: Develop benchmarks, datasets, and evaluation frameworks to rigorously measure model performance.
  • Leverage modern AI techniques: Stay at the frontier of LLMs and applied AI, incorporating new methods where they meaningfully improve outcomes.
  • Collaborate cross-functionally: Partner with engineering, product, and legal teams to ensure research efforts align with real-world needs.
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