About zaimler
AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it.
zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve.
zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're a small, senior team at the seed stage, deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of AI runs on, we'd love to talk.
About the job
We are looking for a few interns to join us either part-time through the year or Full-time for the summer. The ideal candidate should have an interest and some experience in one or more of the following areas: Knowledge Extraction, Natural Language Understanding, Unsupervised Learning, Information Retrieval, and Fine-tuning LLMs. In this internship, you'll play a critical part in developing and training models, pipelines, and methodologies that power our semantic graph systems. You will get experience working at large-scale real data with the goal of making sense of it and putting structure to it so it is discoverable and understandable to end-users. You will be working with models and techniques that involve LLMs, machine learning, natural language processing, and semantic technologies.
What You Will be Doing
Build and/or use best-in-class models to extract knowledge from heterogeneous sourcesDevelop methods to build and evaluate AI Data GraphsFine-tuning LLMs with domain-specific context Work with data infra engineers to develop the best platform for your needs
Prior Experience
Pursuing a Bachelors/ Masters in CSStartup internship experience is highly preferredInterest in working with and fine-tuning language models such as BERT, LLM, SLMsInterest in working with NLP tools such as spacy, openNLP, openNER, GLiNER, etc.Interest in working with embedding-based retrievalStrong background in the fundamentals of machine learningDeployed and maintained ML, NLP or LLM modelsStrong data manipulation skills using tools such as numpy and pandasGreat communication skills and a team player
Nice to Have
Familiar with LLM ecosystem and best practices of fine-tuning and prompt-engineeringFamiliar working on ML and data in the cloudFamiliar with GPU optimizationFamiliar with docker, k8sFamiliar with ray, vllm
We value builders over résumés. If this role excites you but you don't check every box, we still want to hear from you. zaimler is an equal opportunity employer.