Senior Applied Scientist, Scheduling and Optimization

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About this role

Senior Applied Scientist, Scheduling and Optimization Canada (Remote) MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100 , the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the engineering talent to match. We're looking for a Senior Software Engineer to own the constraint-solving engine behind our Scheduling Agent, one of the most strategic bets on our Planning & Scheduling roadmap. The engine is a Python service built on CP-SAT that takes work orders, technicians, and a mix of hard and soft constraints, and produces a feasible weekly schedule that enterprise maintenance teams can trust. Your focus will be evolving the solver to handle increasingly complex, real-world scheduling scenarios and exposing it as tools for GenAI agent workflows. This is a high-ownership role. You'll have the space to shape the modeling approach, partner closely with product and design on what scheduler users actually need, and ship iteratively against feedback from real enterprise customers. What you'll do - Own and evolve the Python optimization service that powers the Scheduling Agent, modeling, solving, and iterating on the constraint formulation as new use cases emerge. - Design and implement increasingly sophisticated scheduling capabilities: trade and crew constraints, irregular capacity patterns, production downtime windows,

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