Software Engineer, LLM Platform
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.
This would be your dream job if you enjoy doing following:
Design and implement LLMs platform on Kubernetes: Design, build, and maintain an LLM platform on Kubernetes to support large language model tuning and inference, and other emerging LLM technologies. Debug complex distributed system problems: Dive deep into complex distributed system problems on Kubernetes outside your direct access, for example, debugging on a customer’s own Kubernetes cluster without kubectl.Solve customer problems: Fast response to customer requests and empathy to customers. Write comprehensive documentation to help customers better use the product.Maintaining internal GPU fleet: Kubernetes-based cluster management system for managing GPU server clusters in our private data center.Collaborate with ML & app engineers and product managers on platform features: Work closely with machine learning engineers, application engineers, and product managers to understand requirements and implement solutions. We are looking for someone with the following qualifications
Education: Bachelor’s degree in Computer Science or comparable fields.Communication: Excellent written and verbal communication. Effective information sharing to audiences with vastly different backgrounds.Experience: 4+ years of professional software engineering experience. Built and shipped software in production environments. Demonstrated experience in building complex systems using open-source tools & systems on the Kubernetes platform and evolving these systems to accommodate fast changes in customer requirements.Languages: Proficient in Python, or other comparable languages. Familiarity with multiple languages.Maintain good engineering quality: Clear and readable coding style in Python or comparable programming languages, ensure thorough and effective testing, comprehensive and straightforward documentation, holistic thinking of the long-term impact of the system.LLM: Understand key concepts in LLMs. Can follow what’s going on in the market. Understanding of how LLM training and inference works. Understand distributed training and inference. Understand RAG, Agents, and other LLM application paradigms.Team spirit: A collaborative mindset and desire to achieve top-tier results. To an inclusive team environment. Be serious, sharp focus, and be a solid team player.Broad understanding of the Kubernetes ecosystem. ML systems, data pipeline, workload management, CI/CD, observability Bonus points if you have experiences in
Experience in building LLM platforms or similar systems.Experience in training/tuning LLMs (pre-training, post-training, fine-tuning)Experience in delivering software products to enterprise customers. 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 $200,000, 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.
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