Explainable AI Engineer
- Role
- AI / ML
- Employment
- Contract
- Company size
- Startup
Open to US only. Set where you work from to check your eligibility.
No BS summary
Build and validate explainable-AI business-impact predictions using operations-research and probabilistic methods; hands-on with MATLAB and simulation-based V&V. Must be a U.S. citizen able to handle DoD Controlled Unclassified Information; remote within the USA. Experience in production mission-critical analytics and strong technical documentation skills required.
Core skills
Required skills
Optional skills
We’re an Industrial AI start-up founded by a Stanford professor and led by recognized leaders in Data Intelligence for Aerospace & Defense supply chain operations. Our Enterprise SaaS AI Application improves sustainment of the U.S. Air Force’s 5,000-aircraft fleet ($100B yearly budget). Having delivered $200M+ in cost avoidances, we are growing 4x in repeat contracts. We have built and are operationally deploying hallucination-free Agentic AI for mission critical decision support that relies on proprietary Explainable AI engines for SME-explainable insights from existing data.
We’re hiring an Explainable AI Engineer to build, verify, and validate business impact predictions based on outputs of our AI Engines. 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 Operations Research features for the AI models Automation of data management 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 business impact prediction 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
Must-haves Experience building mission-critical analytical applications, working in a production environment Hands-on skills in at least some of mathematical methods in: Operations Research Bayesian statistics Monte Carlo analysis Mathematical optimization Decision and Control Experience with MATLAB Model-based development / simulation-based verification Solid experience writing technical documentation Strong collaboration and communication skills; experience working with a software team Graduate Degree in Engineering or a related field U.S. Citizenship . Pluses Supply chain and/ or sustainment in the aerospace industry Experience with Java and GitHub (Actions) Building SaaS applications Experience with GenAI and LLM augmentation (RAG) PhD
US Citizenship Required: This position requires the ability to work with Controlled Unclassified Information for the Department of Defense. A background check and a drug check may be required. Location: This is a remote position. USA, Nationwide. You will have an opportunity to start as a contractor (preferred; full-time or part-time, at least 10 hours/ week), or a full-time employee.
What you'll do
- Understand, develop, & support business impact prediction 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
What they require
- Experience building mission-critical analytical applications, working in a production environment
- Hands-on skills in at least some of mathematical methods in: Operations Research, Bayesian statistics, Monte Carlo analysis, Mathematical optimization, Decision and Control
- Experience with MATLAB
- Model-based development / simulation-based verification experience
- Solid experience writing technical documentation
- Strong collaboration and communication skills; experience working with a software team
- Graduate Degree in Engineering or a related field
- U.S. Citizenship (required); ability to work with Controlled Unclassified Information for the Department of Defense; a background check and a drug check may be required
- Preferred: Supply chain and/or sustainment experience in the aerospace industry
- Preferred: Experience with Java and GitHub (Actions)
- Preferred: Building SaaS applications
- Preferred: Experience with GenAI and LLM augmentation (RAG)
- PhD (plus)
Benefits
- Opportunity to learn from Stanford and Georgia Tech professors
- Option to start as a contractor (preferred) or as a full-time employee; part-time possible (at least 10 hours/week)
We’re an Industrial AI start-up founded by a Stanford professor and led by recognized leaders in Data Intelligence for Aerospace & Defense supply chain operations. Our Enterprise SaaS AI Application improves sustainment of the U.S. Air Force’s 5,000-aircraft fleet ($100B yearly budget). Having delivered $200M+ in cost avoidances, we are growing 4x in repeat contracts. We have built and are operationally deploying hallucination-free Agentic AI for mission critical decision support that relies on proprietary Explainable AI engines for SME-explainable insights from existing data.