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# Founding AI/ML Engineer

- **Company:** David Joseph & Company
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $125,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Information Engineering, Data Security, Data Systems, Distributed Systems, Python (Programming Language), Software Deployment, Data Streaming, Systems Architecture, TypeScript, Unstructured Data, Pytorch, Delivery Pipeline, Large Language Models, Backend, Fastapi, Machine Learning Operations
- **Published:** July 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=4964e6c8c75594ca

## About the Role

* 4-6+ years of engineering experience, ideally 2+ in applied ML
 * Strong Python backend + ML ops familiarity (FastAPI, LangChain, PyTorch, etc.)
 * U.S. work authorization and willingness to undergo FBI background check
 * Deep technical communication skills (can explain systems and trade-offs clearly)
 * Production experience deploying LLMs/VLMs or custom ML inference pipelines
 * Experience understanding and scaling backend infrastructure (does not have to be an expert but must have solid knowledge)

Green Flags

 * Built secure, distributed backend systems (Python/Go/TypeScript)
 * Demonstrated curiosity across both infrastructure and model-level work
 * Worked on real-time or high-throughput data systems
 * Prior early-stage or mission-driven startup experience
 * SWE and data engineering experience/knowledge

Red Flags

 * Only academic or research exposure to AI (no production deployment)
 * Preference for large-company processes or siloed work
 * Weak understanding of data security / compliance requirements

## Description

An early engineer role building the company's AI backbone - processing massive video, audio, and text datasets to surface investigative leads across backend infrastructure and applied ML.

What you'll be doing

 * Build retrieval pipelines over large-scale video, audio, and text datasets
 * Integrate LLMs/VLMs and deploy secure, distributed systems in sensitive environments
 * Ship end-to-end, from data flow design through production deployment
 * Surface investigative signals and leads from unstructured data
 * Work closely with founders on system architecture and technical direction

Tech stack: Python, FastAPI, LangChain, PyTorch; LLM/VLM inference; distributed backend infrastructure


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