Location: Menlo Park,CA, USA
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. About the role: We are looking for exceptionally talented Machine Learning Engineers to join our small team. You will be responsible for end-to-end ownership of scalable Machine Learning systems - from data pipelines, to training, to analyzing performance in a production environment. Since you'll be joining an early-stage startup at the ground level, you'll need to be able to wear multiple hats and thrive while working in a dynamic environment. Design and train new production-ready machine learning models. You will lead the development of new machine learning models and data pipelines. You will apply fundamental machine learning concepts to quickly iterate and debug model related issues and develop new techniques to handle unique cases with each customer. Collect, process and analyze data. A big part of our machine learning projects is understanding and analyzing the data. You must build pipelines and processes for cleaning and organizing data as well as build tools to help analyze data. You must also understand what types of data models are struggling with and use this analysis to propose solutions. Analyze and improve existing models. You will also be responsible for analyzing performance of our existing models and work to improve their accuracy by applying the latest published research, feature engineering and tuning of hyperparameters. Must to have: At least 5+ years of professional experience designing, training, and deploying machine learning models Strong computer science foundation, including data structures, algorithms, and design patterns Expertise in Python demonstrated by implementing multiple medium to large-scale projects Proven ability to implement and debug machine learning models Excellent communication skills and the ability to have in-depth technical discussions with both the engineering team and business people Familiarity with machine learning frameworks and libraries (e.g., scikit-learn, Keras, TensorFlow, PyTorch) Industry experience with relational databases and SQL-based tools BSc in Computer Science, Mathematics or similar field; Master's or Ph.D. degree is a plus Self-starter and comfortable working in an early-stage environment Nice to have: Experience with big data pipeline technologies such as BigQuery, SnowFlake, Spark, Kafka Research experience in machine learning or artificial intelligence related field Contributions to open source ML projects Experience working on logistics or shipping-related products Experience with Agile development $150,000 - $250,000 a year 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. 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.