Optimization Performance Specialist

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. Fastbreak AI is the world leader in sports league scheduling. Our customers include the NBA, NHL, MLS, La Liga, and more than 60 top leagues, each facing some of the most complex scheduling challenges in sports. We are an innovative, collaborative team looking for extraordinary people who enjoy solving big challenges. Why This Position Is Exceptional You’ll partner directly with the world’s largest sports leagues on real, high-stakes scheduling challenges. You own the benchmark “truth set” that steers our optimization roadmap. You’ll work with a collaborative, intellectually rigorous and passionate team where the best idea wins. Your impact will be visible on screens and scoreboards everywhere. What You’ll Do You’ll 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. You’ll be responsible for developing, maintaining and expanding the benchmarking frameworks that measure Fastbreak AI’s performance across a wide variety of scheduling and optimization workloads. You will 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. This role blends deep algorithmic understanding, data‑driven analysis, and hands‑on experimentation. 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. 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. Location Charlotte, North Carolina. Relocation assistance is available. Highly competitive salary and equity package (stock options). Great health, dental and vision insurance and employer‑match 401(k). Read more about Fastbreak AI's benefits, mission and culture. Measure what matters, prove it with benchmarks and ship performance improvements that scale to match our rapid growth. Apply now to help us define the next frontier of intelligent sports optimization. We are an equal opportunity employer. Fastbreak AI complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status or any other category protected by applicable federal, state or local laws. #J-18808-Ljbffr Alumni Ventures