Machine Learning Engineer

An MS or PhD in Computer Science, Machine Learning, or a related field with a focus in ML/AI.
2+ years of professional software engineering experience.
Practical experience with traditional NLP techniques and modern LLM architectures.
Proficiency with Python, PyTorch/TensorFlow, and ML deployment pipelines.
Direct experience building and fine-tuning language models for specialized domains.
Strong experience designing effective evaluation metrics for NLP systems.
Strong communication and collaboration skills.
A self-starting, problem-solving approach biased towards action and scope minimization.

Build ML models and pipelines with scalability and reproducibility as foundational principles, not afterthoughts.
Develop NLP systems that can accurately process and understand complex legal language and terminology.
Design and implement LLM-based solutions that are well-documented, and empower legal professionals to extract valuable insights.
Extend and create reliable model evaluation frameworks that ensure accuracy and reduce the risk of model drift or bias.
Simplify complex ML systems into more manageable solutions that are easier to understand, maintain, and explain.
Optimize model performance through smart feature engineering and efficient algorithm selection based on actual use cases.
Work with security engineers to implement responsible AI practices that protect sensitive data while still delivering valuable insights.

You have experience implementing ML systems in regulated industries.
You have experience optimizing model performance and resource utilization in data-intensive environments.
You have a strong background in legal text analysis or have worked with legal domain experts.
You have experience with few-shot learning and prompt engineering techniques.
You are interested in language, law, finance, or economics.
You thrive in a high-leverage, fast-paced environment.