Senior Applied Scientist, Parts Intelligence, Inventory Optimization

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of and enhance the optimization and machine learning models that drive Parts Agent functionalities: reorder point prediction, economic order quantity, multi-site stock balancing, and demand forecasting.

• Design and execute increasingly advanced inventory intelligence solutions: vendor lead time modeling, criticality-weighted safety stock, substitution graph traversal, and proactive stockout notifications.

• Develop and sustain APIs and tools that integrate these models into GenAI agent workflows (tool calling, structured input/output), empowering the Parts Agent to perform grounded and explainable actions.

• Collaborate with product management and design teams to convert complex real-world inventory challenges into manageable models, and challenge assumptions when "optimal" does not align with operators' needs.

• Engage with real users through design collaborations and pilot programs. Take into account feedback from parts managers and procurement teams and incorporate it into the model.

• Contribute to the broader Python service: focusing on performance, observability, testing, and the reliability of the inventory intelligence runtime.

• Influence how parts intelligence integrates with the overall MaintainX product over time, leveraging historical usage and purchasing data to continually refine model inputs.

⛳️ Requirements

• A minimum of 5 years of professional experience in software engineering or data science, with a substantial focus on optimization, forecasting, or machine learning systems delivered to actual users.

• Strong proficiency in at least one optimization methodology (LP/MILP, stochastic programming, simulation) and practical expertise in demand forecasting or inventory management models.

• Proficient in Python service engineering: APIs, asynchronous programming, testing, profiling, and observability. You are capable of managing a production service from start to finish.

• An academic background in Operations Research, Industrial Engineering, Supply Chain, Statistics, or a related quantitative discipline; a robust undergraduate foundation at a minimum.

• Demonstrated experience in refining data-driven systems with real users — you understand the impact of a rejected model recommendation and have adapted your approach accordingly.

• A product-oriented mindset with a focus on delivery: you ship, measure, and iterate. You prioritize operator outcomes over mere metrics.

• Ability to navigate ambiguity. You can collaboratively design the data model and feature schema with the team rather than waiting for a finalized specification.

• Familiarity with GenAI tools (LLM tool calling, structured output, and prompt design for constrained generation) is expected.

🏝️ Benefits

• Competitive salary and significant equity prospects.

• Comprehensive healthcare, dental, and vision coverage.

• Enrollment in a 401(k) / RRSP program.

• Flexible paid time off (PTO) policy.

• A collaborative work culture where you will engage with colleagues from around the world who embody the MaintainX values: Smart Humble Optimists. We uphold a meritocracy where ideas and efforts are recognized and celebrated.