Machine Learning Intern (Summer 2026)

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 sources Develop methods to build and evaluate AI Data Graphs Fine-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 CS Startup internship experience is highly preferred Interest in working with and fine-tuning language models such as BERT, LLM, SLMs Interest in working with NLP tools such as spacy, openNLP, openNER, GLiNER, etc. Interest in working with embedding-based retrieval Strong background in the fundamentals of machine learning Deployed and maintained ML, NLP or LLM models Strong data manipulation skills using tools such as numpy and pandas Great communication skills and a team player Nice to Have Familiar with LLM ecosystem and best practices of fine-tuning and prompt-engineering Familiar working on ML and data in the cloud Familiar with GPU optimization Familiar with docker, k8s Familiar 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Created: 2026-03-04