Lamini enables every enterprise to safely, quickly, and cost-effectively build their own Expert AI. Our customers own their own models, trained on their data. Lamini optimizes for Expert AI workloads with minimal hallucination, enterprise-grade security, and enterprise flexibility, running on any infrastructure. Our team is made up of highly committed engineers, researchers, and tech industry veterans excited by mission and technology. We’re backed by leading VCs as well as computing and technology companies.
As a Customer-Facing Machine Learning Engineer, you’ll work directly with enterprise customers to leverage Lamini platform to develop and deploy LLM solutions that drive business value. This role blends technical expertise, customer collaboration, and problem-solving to ensure customers achieve maximum benefit from our platform. You will play a pivotal role in bridging the gap between our engineering team and customers, providing technical support, gathering feedback, and leading implementation efforts.
At Lamini, a competitive base salary is part of our comprehensive compensation package, which includes equity and benefits. For this role, the base salary range is $150,000 to $250,000, determined by your skills, qualifications, experience and internal benchmarks.
About the role:
You may be a good fit if you have:
At Lamini AI, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants without regard to race, color, religion, sex, pregnancy (including childbirth, lactation and related medical conditions), national origin, age, physical and mental disability, marital status, sexual orientation, gender identity, gender expression, genetic information (including characteristics and testing), military and veteran status, and any other characteristic protected by applicable law. Lamini AI believes that diversity and inclusion among our employees is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. Selection for employment is decided on the basis of qualifications, merit, and business need.