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Founding Machine Learning Engineer
2 months ago
We're a seed-funded AI startup on a mission to bridge the gap between enterprise business knowledge and data. Our goal is to democratize data discovery and curation, preparing organizations for the era of generative AI.
Today's 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're committed to making enterprise data AI-ready faster, more reliably, and with a stronger foundation of factual semantic knowledge. This leads to more accurate models, superior outcomes, and better business results.
About the JobWe're 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. 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.
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
- 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
- Experience working with spark, scala
