AI Engineer Intern

About Eudia: Eudia is redefining the future of legal work with AI-powered Augmented Intelligence, enabling Fortune 500 legal teams to move faster, manage risk more effectively, and unlock new business value. Backed by $105M in Series A funding led by General Catalyst, we’re building a category-defining platform that blends AI-driven automation with human expertise, transforming legal from a cost center into a strategic growth driver. At Eudia, we move fast. Unlike traditional enterprise software, our teams ship solutions in days, not months—delivering real impact for some of the world’s largest companies, including Cargill, Coherent, DHL, and Duracell. We’re solving one of the most complex, unsolved challenges in AI: bringing trust, accuracy, and security to legal automation. We’re a team of builders, operators, and problem-solvers who are passionate about reshaping an industry that has long been resistant to change. If you’re looking for a place where you’ll be challenged, take ownership from day one, and work alongside some of the brightest minds in AI and legal —we’d love to meet you. About the Role: We are seeking a highly motivated and innovative AI Engineer Intern for either the spring or summer to join our growing team in Palo Alto. This internship offers an exceptional opportunity to work on challenging Machine Learning / Gen AI problems in the legal domain. As an [... source excerpt omitted ...] acy, reliability, and performance. This is a hands-on opportunity to contribute to real-world AI applications, tackle fundamental challenges in deep learning, and gain exposure to production-grade AI systems. As an intern, you will work alongside experienced engineers and professionals to solve real-world problems, create impactful AI solutions, and learn from the best in the field. Key Responsibilities: Assist in designing and implementing AI/ML solutions to address customer-specific challenges. Collaborate with senior engineers to build, test, and deploy machine learning models in production environments. Support the development of cloud-agnostic and secure enterprise-grade [... source excerpt omitted ...] . Help develop and maintain documentation for AI workflows and deployment processes. Provide input on product development and contribute to enhancing the AI/ML product roadmap. Qualifications: Currently pursuing a Bachelor's or Master's in Computer Science, Machine Learning, AI, Mathematics, Statistics, or a related field. Experience with traditional machine learning, deep learning, LLMs, Retrieval-Augmented Generation (RAG), or other NLP techniques. Familiarity with MLOps practices and tools such as MLflow for monitoring and deploying machine learning solutions. Exposure to real-world projects involving data analysis, predictive modeling, or automation. Interest in the legal t