Founding Machine Learning Engineer
Description For Founding Machine Learning Engineer
Zaimler is an innovative startup backed by top VC funds, focused on revolutionizing enterprise data preparation for the AI era. They're building solutions to bridge the gap between enterprise business knowledge and data, making it AI-ready faster and more reliable. The company is seeking a Founding Machine Learning Engineer to join their team of seasoned data infrastructure and machine learning experts from prestigious companies like LinkedIn, Visa, Truera, Hive, and Branch.
The role requires expertise in Knowledge Extraction, Natural Language Understanding, Unsupervised Learning, Information Retrieval, and Fine-tuning LLMs. As a Founding Machine Learning Engineer, you'll be instrumental in developing and training models, pipelines, and methodologies that power their semantic graph systems. The position demands strong technical skills in machine learning, particularly in NLP and LLMs, with hands-on experience in production environments.
The ideal candidate should be based in the Bay Area or willing to relocate, bringing at least 3 years of relevant experience in machine learning and text processing. You'll work alongside data infrastructure engineers to build robust platforms and contribute to shaping the future of enterprise AI. This is an excellent opportunity for someone passionate about solving complex data challenges and working with cutting-edge AI technologies in a startup environment.
Responsibilities For Founding Machine Learning Engineer
- 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 For Founding Machine Learning Engineer
- MS degree in CS or equivalent
- 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
