<p><strong>Robert Half is seeking licensed attorneys or JD candidates to join an ongoing legal research initiative as Legal AI Editor team. </strong></p><p> </p><p><strong>Project information:</strong></p><p>· <strong>Start:</strong> April 27th</p><p>· <strong>Duration:</strong> 4 months with possibility of extension</p><p>· <strong>Pay:</strong> $25</p><p>· <strong>Location</strong>: Remote</p><p>· <strong>Hours</strong>: 40 hours per week, M-F (No part-time opportunities available)</p><p> </p><p><strong>Responsibilities include:</strong></p><p>This project will test the outputs from a Large Language Model (LLM) that is being tested for the creation of AI generated research answers, draft US legal content, including memos and briefs; and summaries of US legal content types, including opinions and statutes. The editors will be asked to evaluate the accuracy of both the answer, summary, or draft content, and any statutory rules or case citations contained within the output. For both tasks, editors will be required to provide assessment rating feedback and to provide additional feedback commentary as necessary.</p><p> </p><p> </p>
<p>We are seeking a skilled AI Engineer to join our dynamic technology team. The ideal candidate has hands-on experience integrating advanced AI and large language model (LLM) features into applications, as well as a strong background in designing and delivering AI-driven solutions. In this role, you will work closely with product, engineering, and data teams to build and enhance innovative products using the latest AI frameworks and tools.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p><br></p><ul><li>Design, develop, and integrate AI and LLM features into new or existing applications, ensuring scalable and reliable deployment.</li><li>Collaborate with cross-functional teams to define technical requirements and deliver AI-driven functionalities in production environments.</li><li>Utilize AI frameworks, APIs, and platforms such as OpenAI, LangChain, vector databases, and machine learning libraries to accelerate solution development.</li><li>Lead prompt engineering, fine-tuning, and model optimization initiatives to improve performance and user outcomes.</li><li>Evaluate and select the most appropriate AI/ML models, tools, and platforms for project needs.</li><li>Conduct documentation, code reviews, testing, and performance monitoring of AI-driven products.</li><li>Stay up to date with advancements in artificial intelligence, generative models, and industry best practices.</li></ul><p><br></p>