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 Machine Learning Engineer to join our team who is based in the Bay Area or willing to move. The ideal candidate should have expertise in one or more of the following areas: Knowledge Extraction, Natural Language Understanding, Unsupervised Learning, Information Retrieval, and Fine-tuning LLMs. In this role, you'll play a critical part in developing and training the models, pipelines, and methodologies that power our semantic graph systems. We're looking for someone with a strong background in machine learning, natural language processing, LLMs, and semantic technologies, with a proven track record of tackling complex, large-scale machine learning projects.

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

MS degree in CS or equivalent

Startup experience is highly preferred

3+ yrs experience in Machine Learning or Knowledge Extraction

3+ yrs experience working with text

Experience working with and fine-tuning language models such as BERT, LLM, SLMs

Experience with NLP tools such as spacy, openNLP, openNER, GLiNER, etc.

Experience with embedding-based retrieval

Strong background in the fundamentals of machine learning

Deployed and maintained ML, NLP or LLM models in production

Strong data manipulation skills using tools such as numpy and pandas

Great communication skills and a team player

Familiar with LLM ecosystem and best practices of fine-tuning and prompt-engineering

Experience working on ML and data in the cloud

Experience with GPU optimization

Experience working with docker, k8s

Experience working with ray,vllm

Senior Applied MLE

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