> Markdown version of [/jobs/ext/3581785-senior-machine-learning-engineer-nlp-llm](https://www.wearedevelopers.com/jobs/ext/3581785-senior-machine-learning-engineer-nlp-llm). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer - NLP/LLM - **Company:** Reuters America LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $127,000.0 - $235,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Programming, Content Analysis, Information Extraction, Machine Learning, Language Modeling, Natural Language Processing, Performance Tuning, Tensorflow, Software Deployment, Software Engineering, Model-Driven Development, Feature Engineering, Pytorch, Large Language Models, Model Validation, Agentic-AI, Information Technology, Machine Learning Operations, Natural Language Generation - **Published:** October 4, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18530304?backUrl=%2Fcareer%2F18530304%2FSenior-Machine-Learning-Engineer-Nlp-Llm-New-York-Brooklyn ## About the Role * 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. ## 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., * 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. ## Related Videos - [Outclassing Frontier LLMs at Extracting Information](https://www.wearedevelopers.com/videos/100303-outclassing-frontier-llms-at-extracting-information) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Inside the Mind of an LLM](https://www.wearedevelopers.com/videos/1617-inside-the-mind-of-an-llm) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Who Owns Your Content in the Age of LLMs?](https://www.wearedevelopers.com/magazine/610-who-owns-your-content-in-the-age-of-llms) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)