Explainable AI Engineer

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

Main 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

Qualifications

Must-haves

• 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.

Pluses

• Model-based development / simulation-based verification
• Shell scripting, Golang.
• Experience with GenAI and LLM augmentation (RAG)

Additional Information

US Citizenship Required: This position requires the ability to work with Controlled Unclassified Information for the Department of Defense.

Location: This is a remote position. USA, Nationwide. Proximity to either our Palo Alto, CA or Atlanta, GA office is a plus. 

You will have an opportunity to start as a contractor (full-time or part-time, at least 10 hours/ week), or a full-time employee.