Senior Machine Learning Engineer

Senior Machine Learning Engineer – LLMs & NLP | Legal Document Intelligence

Location: Remote (US) or hybrid from New York City

I’m recruiting for a global leader in professional information and enterprise software, and they’re looking for a hands-on ML Engineer who has actually built, trained and shipped models into production. Not just experimented with them.

The opportunity

You’ll join a highly technical ML team building production ML and LLM systems that pull insight out of complex legal documents: contractual language, information extraction, and comparisons across huge document collections. You’ll work alongside ML engineers, legal subject matter experts, product engineers, and data and security partners.

What you’ll do

• Design, build, train and deploy ML and LLM-based systems for hard NLP and document intelligence problems
• Ship production solutions across information extraction, summarisation and text generation, AI agents, search and document analysis
• Build scalable, reliable ML pipelines covering training, evaluation, deployment and ongoing production use
• Develop rigorous evaluation frameworks to measure quality, accuracy, reliability, drift and bias
• Optimise model performance and resource use through experimentation, feature engineering, model selection and tuning
• Turn complex product and business problems into practical ML solutions, taking them from experiment to production at scale
• Work across ML, engineering, product, legal domain, data and security teams to deliver reliable AI while protecting sensitive information

What you’ll bring

• Master’s degree in Machine Learning, Computer Science, Statistics or a related quantitative field, with a focus on ML or AI
• 5+ years in ML engineering, applied ML, research engineering or closely related software engineering
• Proven hands-on experience building, training and deploying models into production, and the ability to clearly explain your individual contribution from model development to deployment
• Strong practical experience with ML, NLP and modern LLM architectures
• Experience in at least one of: information extraction, text generation/summarisation, AI agents or search
• Advanced Python and hands-on experience with PyTorch or TensorFlow
• Experience developing or fine-tuning language models for specialised domains
• Experience designing and applying evaluation methods and metrics for production ML systems
• Strong communication, able to explain technical decisions, trade-offs and outcomes to technical and domain teams

Bonus points

• PhD in ML, Computer Science, Statistics or a related field
• Experience deploying and operating ML or LLM systems at scale
• Legal tech, legal NLP or other domain-specific language modelling
• ML in financial services, economics or other regulated, data-sensitive industries
• Serving or self-hosting LLMs and optimising for performance and compute efficiency
• A track record of taking complex ML initiatives from research to production with measurable business impact