Staff Software Engineer, Capacity Optimization

Infrastructure Modeling & Automation

You will design and build production-grade systems and pipelines to automate capacity planning, demand management, and quota allocation.

Quantitative Forecasting

You will implement and maintain sophisticated models for infrastructure demand forecasting, incorporating architectural shifts, peak loads, and time-shifting opportunities.

Resource Optimization Algorithms

You will develop and deploy algorithms to optimize resource utilization across a heterogeneous fleet (CPU, GPU, TPU) and diverse supply models (on-demand vs. reserved).

Data Pipeline Engineering

You will architect and maintain robust data pipelines that ingest infrastructure telemetry and demand driver signals to feed forecasting and optimization engines.

Outcome Analysis

You will build systems to translate resource plans into tangible outcomes (e.g., queue lengths, user demand fulfillment) and develop attribution models for capacity imbalances.

Cross-Functional Collaboration

You will partner with Simulation, Infrastructure, and Finance teams to translate business requirements into technical specifications and automated solutions.

Technical Leadership

You will provide technical guidance on the intersection of quantitative modeling and systems engineering, mentoring junior members and influencing the technical roadmap for SCORPIO.

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, Operations Research, or a related quantitative field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on distributed systems, large-scale data processing, or quantitative engineering.
• Proficiency in C++ or Python, with experience building and deploying production-level software.
• Experience with large-scale distributed systems and cloud infrastructure (e.g., GCP, AWS, Azure).
• Strong background in quantitative methods, such as optimization, statistical modeling, or time-series analysis.
• Expertise in SQL and working with large-scale data warehouses (e.g., BigQuery).

Preferred Qualifications

• PhD or Master's degree in a quantitative field or Computer Science.
• Experience in Capacity Engineering, Infrastructure Optimization, or Site Reliability Engineering at scale.
• Familiarity with ML-driven forecasting and optimization techniques.
• Experience with financial modeling or cost-benefit analysis of technical infrastructure.
• Experience building automation tools for resource management and quota allocation.
• Knowledge of simulation workloads or high-performance computing (HPC) environments.

Pay

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level.