Casetext has led innovation in legal AI since 2013, applying cutting-edge AI to the law to create solutions that enable attorneys to provide higher-quality representation to more clients, enhance efficiency and accuracy, and gain a competitive advantage. Our leadership and contributions in legal AI have been recognized worldwide, including receipt of the World Economic Forum’s Technology Pioneer award for the development of AI-powered brief analysis tool CARA AI. Today, over 10,000 law firms—from solos and small practices to more than 40 Am Law 200 firms—rely on Casetext to elevate the quality of their law practice. For more information visit www.casetext.com. About the Role Casetext is revolutionizing the field of legal research by combining state-of-the-art machine learning and natural language processing technologies. Our platform helps millions of users access high-quality, affordable legal information and insights. We aim to disrupt the traditional legal research landscape and improve access to justice. We're looking for a Senior Machine Learning Researcher who is passionate about leveraging cutting-edge technologies in natural language understanding, neural information retrieval, graphical deep learning, and Large Language Models (LLMs) to better our justice system. This role is entirely remote, but you must be based in the U.S. and authorized to work in the U.S. As the Sr. ML Researcher You Will: Research Development: Understand challenges in the legal tech sector and design machine learning-based solutions to tackle them. Stay updated with the latest in ML/NLP research, and identify promising avenues for improvement in Casetext’s offerings, including interaction with Large Language Models. Experimentation: Design and execute experiments to quantitatively assess improvements over existing baselines in search algorithms and generative AI technologies for legal applications. Modeling Deployment: Work closely with our engineering team to implement, train, and deploy machine learning models in production, including those based on Large Language Models. Evaluate and vet solutions offered by external vendors to improve our AI offerings. Team Collaboration: Guide, mentor, and develop less experienced colleagues. Work cross-functionally with team members, including those in Product Management, Engineering, and Marketing. Publication Outreach: Publish novel research and findings in top ML/NLP venues, and maintain a presence in the scientific community. Data Management: Oversee data collection and annotation pipelines and work with messy structured and unstructured datasets. About You: Proficient in SQL, SciKitLearn, PyTorch, Huggingface, and other standard ML, NLP, and deep learning libraries Strong proficiency in scripting languages (Python Bash) Track record of solving real-world problems and previous publications in ML/NLP conferences or journals Familiarity with Large Language Models and techniques for interacting with them (e.g., advanced prompting) Experience deploying distributed machine learning systems on AWS, Google Cloud Platform, or similar platforms Comfortable working with messy structured and unstructured datasets and experimenting in settings with limited labeled data Able to work iteratively and quickly within our fast-paced product development cycles and maintain a results-oriented mindset Familiarity with software engineering practices and writing clean code Prefer someone with publications in top ML conferences journals, but not required Prefer someone proficient in a compiled language, such as Scala, Java, Rust or C++ Looking for someone with excellent communication skills who is able to articulate technical concepts clearly to both technical and non-technical stakeholders Team player, open to giving and receiving constructive feedback, and experience in mentoring junior team members Self-starter/Driven: capable of independently identifying, pursuing, and delivering on research directions Someone with a sincere interest and passion for NLP, generative AI, and knowledge retrieval, especially for the legal domain A Ph.D. in Computer Sciences, Data Science, Machine Learning, Math, Physics, or a related quantitative field. Alternatively, an MS with a strong technical background and research experience (i.e., publications). What's in it For You? You will join our inclusive culture of world-class talent, where we are committed to your personal and professional growth through: 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 Wellbeing: Comprehensive benefit plans; flexible and supportive benefits for work-life balance: flexible vacation, two company-wide Mental Health Days Off; work from another location for up to a total of 8 weeks in a year, 4 of those weeks can be out of the country and the remaining in the country, Headspace app subscription; retirement, savings, tuition reimbursement, and employee incentive programs; resources for mental, physical, and financial wellbeing. Culture: Globally recognized and award-winning reputation for equality, diversity and inclusion, flexibility, work-life balance, and more. Learning Development: LinkedIn Learning access; internal Talent Marketplace with opportunities to work on projects cross-company; Ten Thousand Coffees Thomson Reuters café networking. Social Impact: Eight employee-driven Business Resource Groups; two paid volunteer days annually; Environmental, Social and Governance (ESG) initiatives for local and global impact. Purpose Driven Work: We have a superpower that we’ve never talked about with as much pride as we should – we are one of the only companies on the planet that helps its customers pursue justice, truth and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. #LI-AY1 In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and ADD insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan. Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The location(s) for this role include one or more of the following metro locations: Los Angeles, New York City, San Francisco, Washington, DC. The base compensation range for the role in any of those locations is $184,800 - $343,200. The location(s) for this role include one or more of the following states: CA, CO, CT, IL, NV, TX, WA and/or remote. The base compensation range for the role in any of those locations is $168,000 - $312,000. This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance. Base pay is positioned within the range based on several factors including an individual’s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs. En Thomson Reuters creemos que lo que hacemos importa. Nos apasiona nuestro trabajo , inspirados por el impacto que tiene en nuestro negocio y en nuestros clientes. Como equipo , creemos en ganar como uno solo; colaborando para alcanzar objetivos compartidos y desarrollando experiencias desafiantes y significativas . Con más de 25.000 empleados en más de 100 paises , trabajamos con flexibilidad a través de las fronteras y realizamos innovaciones que ayudan a dar forma a las industrias de todo el mundo . Hacer que esto suceda es un proceso dinámico y en evolución; contamos con que cada empleado sea un catalizador para impulsar nuestro desempeño y el suyo propio. Como empresa global , confiamos en la diversidad cultural y pensamos en cumplir nuestros objetivos. Para asegurarnos que podemos hacerlo, buscamos talentos, empleados calificados en todas nuestras operaciones alrededor del mundo, independientemente de la raza , color , sexo, identidad y expresión de género , nacionalidad , religión , orientación sexual , discapacidad , edad , estado civil , y/o cualquier otra clasificación protegida según la ley aplicable. Thomson Reuters se enorgullece por ser un empleador con igualdad de oportunidades de empleo/acción, que ofrece un lugar de trabajo libre de drogas . También hacemos adaptaciones razonables para personas calificadas con discapacidades y para creencias religionas sinceras de acuerdo a la ley aplicableble. Protégete de ofertas de trabajo fraudulentas haz click aquí para más información. Podés encontrar más información sobre Thomson Reuters en thomsonreuters.com. Thomson Reuters proporciona a los profesionales la inteligencia , tecnologia y experiencia humana que necesitan para encontrar respuestas confiables . Permitimos que los profesionales de los mercados financieros y de riesgos , legales , fiscales , contables y de medios de comunicacion , tomen las decisiones más importantes , todo ello impulsado por la organizacion de noticas más confiable del mundo. Hear from one of our AI Experts, Shawn Malhotra, Thomson Reuters' Head of Engineering on the key components that go into innovating AI at Thomson Reuters.