Senior Machine Learning Engineer - NLP/LLM

Job Description

As a Senior Machine Learning Engineer , you will build and deploy production machine learning and large language model (LLM) systems that extract actionable insights from complex legal documents and data. You will work on challenging natural language processing problems involving contractual language, information extraction, model-driven analysis, and comparisons across large collections of documents.

You will join a highly technical machine learning team and collaborate with machine learning engineers, legal subject matter experts, product engineers, and data and security partners. This is a hands-on role for someone who has personally built, trained, evaluated, and deployed machine learning models into production and wants to apply that expertise to sophisticated real-world products.

This role may be remote within the United States or hybrid from our New York City office .

Key Responsibilities

Design, build, train, and deploy machine learning and LLM-based models and systems that solve complex natural language processing and document intelligence problems.

Develop production solutions for areas such as information extraction, text generation and summarization, AI agents, search, and document analysis .

Build scalable and reliable machine learning pipelines that support model training, evaluation, deployment, and ongoing production use.

Develop rigorous model evaluation frameworks and metrics to assess model quality, accuracy, reliability, drift, and potential bias.

Optimize model performance and resource utilization through experimentation, feature engineering, model selection, and tuning.

Translate complex business and product problems into practical machine learning solutions and take those solutions from experimentation through production deployment at scale .

Collaborate across machine learning, engineering, product, legal domain, data, and security teams to deliver reliable AI capabilities while protecting sensitive information.

Required Qualifications

Master’s degree in Machine Learning, Computer Science, Statistics, or a closely related quantitative field with a focus on machine learning or artificial intelligence.

3+ years of professional machine learning engineering, applied machine learning, research engineering, or closely related software engineering experience.

Demonstrated hands-on experience building, training, and deploying machine learning models into production , including the ability to explain your individual contribution from model development through production deployment.

Strong practical experience with machine learning, natural language processing, and modern LLM architectures .

Experience with at least one of the following: information extraction, text generation/summarization, AI agents, or search .

Advanced Python programming skills and hands-on experience with machine learning frameworks such as PyTorch or TensorFlow .

Experience developing or fine-tuning language models or other machine learning models for specialized use cases or domains.

Experience designing and applying model evaluation methods and metrics to measure the performance and reliability of production machine learning systems.

Ability to translate product or business problems into machine learning solutions and clearly communicate technical decisions, trade-offs, and outcomes.

Strong problem-solving, collaboration, and ownership skills, with the ability to work effectively across technical and domain-focused teams.

Preferred Qualifications

PhD in Machine Learning, Computer Science, Statistics, or a closely related quantitative field.

Experience deploying and operating ML or LLM systems at scale in production environments .

Experience with legal technology, legal natural language processing, legal document analysis, or other domain-specific language modeling .

Experience applying machine learning within financial services, economics, or other regulated or data-sensitive industries .

Experience serving or self-hosting large language models and optimizing model performance and computational efficiency.

Experience taking complex ML initiatives from experimentation or research through production and demonstrating measurable product or business impact.

#LI-TH1

This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization.

What’s in it For You?

Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.

Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.

Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.

Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.

Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compe