Senior Inventory Intelligence Scientist — Parts Optimization

MaintainX; Austin (TX); On-site; USD 131,000 - 236,000; Full time

Job summary

MaintainX, now part of Autodesk, seeks a Senior Applied Scientist to own the intelligence layer for the Parts Agent. You will build optimization and ML models, design inventory intelligence, and expose tools via APIs to GenAI workflows.

This high-ownership role partners with product and design to address real inventory problems and deploy iteratively with enterprise customers. You will shape modeling approaches, work on forecasting and stock balancing across sites, and improve end-to-end

Qualifications

• 5+ years of professional software engineering or data science experience.
• Strong fluency with optimization paradigms (LP/MILP, stochastic programming, simulation).
• Solid Python service engineering: APIs, async, testing, observability.
• Academic grounding in quantitative fields; strong undergrad foundation.

Responsibilities

• Own optimization and ML models for Parts Agent capabilities like reorder point and EOQ.
• Design inventory intelligence: lead time modeling, safety stock, stockout alerts.
• Build and maintain APIs exposing models to GenAI workflows.
• Collaborate with PM/design to translate real inventory problems into models.
• Iterate with users via partnerships and pilot deployments; reflect feedback.
• Contribute to the Python service reliability, performance, and testing.

Skills

Optimization

Forecasting

ML systems

Python

GenAI tooling

APIs

Education

Operations Research/Industrial Engineering/Statistics degree

Tools

Python

APIs

GenAI tooling

Job description

MaintainX, now part of Autodesk, seeks a Senior Applied Scientist to own the intelligence layer for the Parts Agent. You will build optimization and ML models, design inventory intelligence, and expose tools via APIs to GenAI workflows.

This high-ownership role partners with product and design to address real inventory problems and deploy iteratively with enterprise customers. You will shape modeling approaches, work on forecasting and stock balancing across sites, and improve end-to-end