Cypress HCM is seeking a Machine Learning Engineer to join their Demand Planning team within the FinOps organization. This role focuses on designing and implementing AI/ML-driven forecasting models to predict infrastructure demand, collaborating with various teams to enhance forecasting accuracy and optimize capacity planning.
Responsibilities:
- Develop and deploy AI/ML forecasting models for long-range demand and supply planning
- Enhance accuracy by incorporating multi-metric inputs and hybrid cloud strategies
- Apply advanced techniques: ARIMA, Bayesian models, RNN, LSTM, and hybrid AI approaches
- Build POCs parallel to existing models to validate AI-driven forecasting improvements
- Segment customers using ML for tailored capacity solutions
- Run scenario-based forecasts to optimize scaling and utilization across service tiers
- Collaborate with hardware, infrastructure, and cloud analytics teams to create capacity roadmaps
- Automate workflows for forecasting, reporting, and analytics pipelines
- Own the end-to-end delivery of ML solutions: design, implementation, testing, and deployment
- Provide insights and reports to leadership on forecast variability and model performance
Requirements:
- Python coding
- ML- applied forecasting