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About the Role
Build core Machine Learning (ML)/Natural Language Processing (NLP) systems that transform raw Electronic Record data into actionable insights. Work on cutting-edge Artificial Intelligence (AI) in production, leveraging knowledge graphs, Large Language Models (LLMs), and advanced NLP to solve complex, data-intensive problems in an early-stage startup environment.
Responsibilities
- Build and improve information extractors and summarizers that power end-user applications.
- Scrape, collect, extract, transform, query, analyze, mine, and distill structured/unstructured data to evaluate system quality and performance, draw insights, and expand/refine knowledge graphs.
- Build and improve supporting data/AI/ML systems and automations.
- Develop and deploy secure code, maintaining confidentiality, integrity, and availability of information systems and processes in compliance with applicable laws.
- Participate in rotating on-call duties to ensure system uptime.
Requirements
- 7+ years of full-time experience in AI/ML or full stack software engineering (excluding internships or contract work).
- Experience building and improving production ML/NLP software systems primarily handling text/unstructured data.
- Hands-on experience scraping, collecting, extracting, transforming, querying, analyzing, mining, distilling, and summarizing structured/unstructured data.
- Direct experience improving quality/performance of systems powered by document classifiers, information extraction, cleaning/integration, summarization, retrieval, semantic search, knowledge graphs, statistical/neural machine learning methods, and LLMs.
- Familiarity with highly regulated domains is a plus.
Skills
- Python for data wrangling/munging
- Software engineering
- Structured Query Language (SQL)
- Relational data modeling
- Django Object-Relational Mapping (ORM)
- Data/ML engineering
- AI/ML/NLP/Information Extraction (IE)/Information Retrieval (IR)
- Information extraction/retrieval
- Semantic search
- Knowledge graphs
- Data integration
- Statistical/neural learning
- LLMs
- Generative AI
- PyTorch
- Google Cloud Platform
- NLP techniques and tools
Location
- San Francisco
- Bay Area
Work Type
- Hybrid
Experience Level
- Senior
Education Level
- Computer Science (CS) or Engineering degree
- Advanced degrees in relevant fields are a plus
Salary/Compensations
- $140K - $290K
About the Company
- Early-stage startup where work ships fast, gets direct feedback, and shapes the future of the product.