Senior Parts Inventory Intelligence Scientist

MaintainX; San Francisco (CA); Hybrid; USD 131,000 - 236,000; Full time

Job summary

MaintainX is seeking a Senior Applied Scientist to own the intelligence layer behind its Parts Agent, a strategic element in the Inventory & EAM roadmap. You will design and ship decision models, optimization routines, and AI-powered tools to help enterprise maintenance teams optimize stock, reorder points, and supplier catalogs.

You will collaborate with product and design to ensure practical, explainable, and scalable solutions, while owning production services and building integrations with

Qualifications

• 5+ years in software engineering or data science related to optimization, forecasting or ML systems.
• Strong background in optimization paradigms (LP/MILP, stochastic programming, simulation).
• Solid Python service engineering: APIs, async, testing, observability.

Responsibilities

• Own and evolve the optimization and ML models powering Parts Agent capabilities.
• Design inventory intelligence features: lead time modeling, safety stock, stock balancing.
• Build and maintain APIs/tools exposing models to GenAI workflows and agent calls.
• Collaborate with PM/design to translate real-world problems into tractable models.
• Iterate with users via pilot deployments and incorporate feedback into models.
• Contribute to the surrounding Python service: performance, observability, testing, reliability.

Skills

Optimization

Forecasting

ML Systems

Python

GenAI Tooling

Education

Operations Research

Industrial Engineering

Statistics

Tools

LLM Tooling

Structured Output

Job description

MaintainX is seeking a Senior Applied Scientist to own the intelligence layer behind its Parts Agent, a strategic element in the Inventory & EAM roadmap. You will design and ship decision models, optimization routines, and AI-powered tools to help enterprise maintenance teams optimize stock, reorder points, and supplier catalogs.

You will collaborate with product and design to ensure practical, explainable, and scalable solutions, while owning production services and building integrations with