Senior Applied Scientist, Scheduling and Optimization

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

📋 Description

• Take ownership of and enhance the Python optimization service that drives the Scheduling Agent, modeling, solving, and refining the constraint formulation as new use cases arise.

• Create and implement progressively advanced scheduling functionalities: trade and crew constraints, irregular capacity patterns, production downtime windows, multi-site considerations, and reactive re-scheduling.

• Develop and sustain API routes and tools that connect the solver to GenAI agent workflows (tool calling, structured input/output).

• Collaborate with PM and design teams to convert complex real-world scheduling challenges into solver constraints, and advocate for user needs when "optimal" doesn't align with their expectations.

• Refine the solver through interactions with real users via design collaborations and pilot implementations. Take insights from human schedulers seriously and integrate their feedback into the model.

• Contribute to the broader Python service: enhancing performance, observability, testing, and the reliability of the optimization runtime.

• Help shape the integration of scheduling intelligence with the wider MaintainX product over time, including leveraging execution data to enhance solver inputs.

⛳️ Requirements

• Over 5 years of professional software engineering experience, with considerable focus on optimization, constraint programming, or operations research problems delivered to actual users.

• Strong expertise in CP-SAT and at least one additional optimization paradigm (MILP via Gurobi/CPLEX/HiGHS, metaheuristics, or similar). You have explored the boundaries of one approach and made informed decisions about which methods to employ.

• Proficient in Python service engineering: APIs, asynchronous programming, testing, profiling, and observability. You can manage a production service comprehensively.

• Academic background in Operations Research, Industrial Engineering, Computer Science, or a related quantitative discipline, with at least a solid undergraduate foundation; advanced degrees are common in this field but not mandatory.

• Proven experience in iterating optimization systems with actual users; you understand the implications when a human discards the "optimal" solution and have adapted the model accordingly.

• A product-oriented mindset and delivery focus; you ship products, measure results, and iterate based on feedback. You prioritize user outcomes over merely achieving objective functions.

• Comfortable with ambiguity; you can collaboratively design the constraint data model with the team rather than waiting for a precise specification.

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

🏝️ Benefits

• Competitive salary and substantial equity opportunities.

• Comprehensive healthcare, dental, and vision coverage.

• 401(k) / RRSP enrollment program.

• Flexible PTO policy allowing you to take what you need.

• A work culture where:

• You'll collaborate with individuals across the globe who embody the MaintainX values: Smart Humble Optimists.

• We uphold a meritocracy, where ideas and efforts are openly recognized and celebrated.