Applied Scientist in Scheduling Optimization

Location: Meota

Join Maintain

X as a Senior Applied Scientist and enhance scheduling practices with advanced Python optimization techniques. This role emphasizes real-world application and user feedback.

Your responsibility includes refining the scheduling optimization engine central to Maintain

X's offerings. With a focus on constraint programming, you will tackle complex scheduling scenarios while collaborating with cross-functional teams. Candidates should have over 5 years of software development experience, particularly in optimization and operations research.

Key Responsibilities:

• Evolve and maintain the optimization engine for scheduling tasks
• Develop advanced scheduling features accommodating various constraints
• Create APIs to enable integration with GenAI capabilities
• Work closely with PM and design teams to translate complexities
• Engage with users to gather actionable insights for improvement

Requirements

• Minimum of 5 years in professional software engineering
• Expertise in CP-SAT and related optimization strategies
• Solid background in Python service development
• Past experience with real user-oriented optimization
• Exposure to GenAI tools for workflow improvements

Drive innovation in scheduling solutions and user satisfaction with your expertise at Maintain

X.

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