À propos
Zaimler is building the next-generation semantic platform that links fragmented enterprise data and extracts meaning with knowledge-distilled models. We're creating the foundation for AI systems that don't just generate, but retrieve, link, and reason over enterprise knowledge. In just over a year, we've begun partnering with Fortune 500 design partners in insurance, travel, and technology, deploying our semantic platform into some of the world's most complex and high-volume data ecosystems. Our platform enables enterprises to make their data AI-ready from the start: automating ontology creation, data mapping, and retrieval-augmented reasoning at scale. Our team comes from LinkedIn, Visa, Meta, and Branch, and has spent decades solving data and infrastructure challenges at scale. Backed by top VCs, we're building the next foundational layer for enterprise AI. 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
Compétences linguistiques
- English
Avis aux utilisateurs
Cette offre provient d’une plateforme partenaire de TieTalent. Cliquez sur « Postuler maintenant » pour soumettre votre candidature directement sur leur site.