Senior Applied MLE
zaimler, San Mateo, CA, United States
About zaimler
zaimler is building the 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 semantic AI infrastructure into some of the world’s most complex data ecosystems. Our platform enables enterprises to make 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.
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.
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
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
Nice to Have
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
#J-18808-Ljbffr
zaimler is building the 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 semantic AI infrastructure into some of the world’s most complex data ecosystems. Our platform enables enterprises to make 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.
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.
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
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
Nice to Have
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
#J-18808-Ljbffr