Optimization Performance Specialist

About the role

We are looking for an Optimization Performance Specialist to lead the design, execution and analysis of performance benchmarks across our AI and ML optimization approaches for our sports scheduling platform.

Responsibilities

• Apply your computer science and math skills to determine the best algorithmic approaches for different scheduling problems, determine parameter settings, and work closely with other optimization specialists who develop new approaches to these incredibly challenging problems.
• Develop, maintain and expand the benchmarking frameworks that measure Fastbreak AI's performance across a wide variety of scheduling and optimization workloads.
• Work closely with our research, product and infrastructure teams to ensure that our solvers deliver world-class speed, accuracy and scalability on real-world problems.
• Benchmarking & Evaluation: Design and maintain benchmarking pipelines for different algorithmic approaches across an ever-growing set of highly proprietary benchmark problems. Develop automated tools for parameter tuning, performance profiling, and regression detection.
• Performance Analysis: Analyze algorithmic performance and identify bottlenecks in computation, model formulation, and solver configuration. Generate detailed benchmark reports and visualizations to guide engineering and research decisions. Collaborate with the optimization team to validate algorithmic improvements.
• System Integration: Maintain version-controlled benchmark datasets and metrics repositories. Integrate benchmark testing into CI/CD pipelines for solver components.

Requirements

• MS or PhD in Operations Research, Computer Science, Applied Mathematics, or related field
• 3+ years of experience in software engineering, data analysis and/or managing computational workloads
• Proficiency in Python, scripting, and other programming languages to run experiments, harvest results and extract results & insights
• Strong background in algorithmic performance measurement and statistical analysis
• Familiarity with running workloads on distributed resources (AWS, Azure, etc)
• Experience with git, general software engineering practices

Preferred Experience

• Experience with discrete optimization and benchmarking efforts such as MIPLIB
• Contributions to open-source optimization libraries or benchmark suites