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Eudia is redefining 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, the company is building a category-defining platform that blends AI-driven automation with human expertise, transforming legal from a cost center into a strategic growth driver.
The AI Engineer role is a solutions-minded position focused on working with data from Fortune 500 companies' legal and risk departments. You will develop secure, enterprise-grade software using the latest in Generative AI, tackling challenges in creating cloud-agnostic solutions, maintaining stringent security and compliance standards, and building scalable, resilient platforms for enterprise applications, data, AI, and search.
Key responsibilities include:
- Work closely with customers to understand and address their AI/ML challenges, designing and deploying custom solutions that leverage company technologies
- Act as the primary technical contact, providing hands-on support during deployment and ensuring successful integration
- Collaborate with product management and engineering to convey customer feedback, influencing AI/ML product roadmaps
- Lead the deployment of AI/ML solutions, ensuring smooth integration and ongoing optimization
- Provide technical training to clients, identify challenges in AI/ML deployments, and proactively improve model performance
- Maintain clear communication with all stakeholders, providing regular updates on progress and outcomes
Required qualifications include a Master's or Ph.D. in Computer Science, Machine Learning, AI, Mathematics, Statistics, or related field; 2-5 years of experience in AI/ML engineering, data science, or similar role with strong background in deploying and integrating AI/ML solutions in real-world environments; proficiency in LLMs, RAGs, evaluation techniques, and machine learning frameworks (TensorFlow, PyTorch) and Python; experience with cloud platforms (AWS, Azure, Google Cloud) and ML services; strong problem-solving skills in diagnosing and resolving AI/ML model issues; experience in client-facing roles with excellent communication and interpersonal skills; familiarity with MLOps practices and tools (MLflow) and experience in model deployment, monitoring, and CI/CD of AI/ML solutions; and passion for AI/ML technologies.
