Founding Machine Learning Engineer

2 weeks ago


San Mateo, California, United States Seed-Funded AI Startup Full time
About Us

We are a seed-funded AI startup on a mission to bridge the gap between enterprise business knowledge and data, democratizing data discovery and curation to prepare organizations for the era of generative AI.

Our current data tools are overly complex, poorly integrated, and siloed, forcing AI practitioners and data scientists to spend more time wrestling with tools, relying on tribal knowledge, and navigating data lakes rather than doing meaningful data science work.

We focus on making enterprise data AI-ready faster, more reliably, and with a stronger foundation of factual semantic knowledge, leading to more accurate models, superior outcomes, and better business results.

About the Job

We are seeking a Machine Learning Engineer to join our team. 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.

Key Responsibilities
  • 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
Requirements
  • 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 Haves
  • 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


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