Job description

Machine Learning Engineer

Location: New York, NY (Hybrid)

About the Company

Our client is a high-growth AI company building advanced machine learning systems to solve complex NLP challenges within the global capital markets ecosystem. Founded in 2022 and based in New York, the team combines an in-house ML platform with deep expertise from leading researchers to drive innovation across legal and financial workflows.

The company partners with many of the world’s top law firms and has raised ~$30M to date, with backing from top-tier venture investors. They’ve been featured in major publications including The Wall Street Journal, Bloomberg, and American Banker, and recognized as a top AI company by leading industry outlets.

The Opportunity

Capital markets transactions are highly complex, driven by dense legal documentation that requires precise interpretation across multiple stakeholders. Extracting, structuring, and benchmarking these legal terms is both critical and technically challenging.

Our client is building the infrastructure to solve this problem, leveraging NLP and LLMs to analyze contractual language, identify patterns, and generate insights across large-scale document sets.

The Role

As a Machine Learning Engineer, you will design and deploy production-grade ML systems that extract actionable insights from complex legal and financial data. You’ll work at the intersection of NLP, LLMs, and structured data, collaborating closely with ML researchers, domain experts, and product engineers.

This is a high-impact role where your work will directly shape core product capabilities.

What You’ll Do

Build and deploy NLP systems to process complex legal language
Develop scalable, production-ready ML pipelines with a focus on reliability and reproducibility
Design and implement LLM-based solutions for extraction, summarization, and analysis
Create and maintain robust evaluation frameworks to ensure model performance
Optimize models through feature engineering and algorithm selection
Productionize ML systems for maintainability and clarity
Collaborate cross-functionally with product, legal, and engineering teams
Implement responsible AI practices for sensitive data environments

Required Qualifications

MS or PhD in Computer Science, Machine Learning, or related field
3+ years of production-level software engineering experience
Strong experience with NLP and modern LLM architectures
Experience in areas such as information extraction, summarization, search, or agents
Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow)
Experience building and deploying language models
Strong understanding of evaluation methodologies for NLP systems
Strong communication skills and a pragmatic, execution-focused mindset