Explainable AI Engineer
About The Position
We’re hiring an Explainable AI Engineer to build, integrate, and deploy our AI Engines and Agentic AI workflows. You’ll have an opportunity to learn from Stanford and Georgia Tech professors and work across algorithms and data pipelines to evolve our Explainable AI including Development of deep math features for the models, ML, and inferences Automation of data wrangling and cleansing towards scalability Aerospace grade V&V for mission critical functions using simulations Explainable AI engine interfaces to data, human users, and Agentic AI You’ll start on a consulting basis (at competitive hourly rate), with the opportunity to move into a full-time role with equity as you demonstrate impact.
Requirements
- Experience with productized analytical applications and technical documentation.
- Hands-on skills in at least some of mathematical methods in: Statistics Bayesian estimation Mathematical optimization Decision and Control
- Experience with MATLAB, Java, GitHub (Actions).
- Strong collaboration and communication skills.
- U.S. Citizenship.
Nice To Haves
- Model-based development / simulation-based verification
- Shell scripting, Golang.
- Experience with GenAI and LLM augmentation (RAG)
Responsibilities
- Understand, develop, & support deep math analytics in Explainable AI Engines
- Build, evolve, verify, and validate data processing pipeline segments
- Support scalable deployment of the AI
- Integrate Explainable AI with LLM tools for Agentic AI experience
- Collaborate with the cloud software team and occasionally with customers
- Document Explainable AI for customer users and internal software developers
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What This Job Offers
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
1-10 employees
