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Текст:
Hirify AI/Оригинал
TL;DR
Senior Data Scientist (ML) (Simulation Capacity Optimization): Building production systems and data pipelines for forecasting simulation infrastructure demand, optimizing CPU, GPU, TPU, and storage allocation, and automating quota management with an accent on statistical modeling, time-series analysis, and resource optimization. Focus on designing infrastructure capacity plans, analyzing queue and demand-fulfillment outcomes, and translating quantitative models into reliable, cost-effective automation.
Location: On-site in Mountain View, California, United States
Base salary: $213,000–$263,000 USD per year, plus eligibility for an annual bonus, equity incentive plan, and company benefits.
Company
Waymo develops autonomous driving technology and operates a fully autonomous ride-hail service powered by the Waymo Driver.
What you will do
Build production systems and pipelines for simulation capacity planning, demand management, and quota allocation.
Develop quantitative forecasting models for infrastructure demand, peak loads, architectural changes, and time-shifting opportunities.
Design and deploy optimization algorithms for CPU, GPU, and TPU utilization across on-demand and reserved supply.
Architect data pipelines that ingest infrastructure telemetry and demand-driver signals.
Analyze resource-plan outcomes such as queue lengths and user-demand fulfillment, including attribution of capacity imbalances.
Partner with Simulation, Infrastructure, and Finance teams while providing technical guidance and mentoring junior members.
Requirements
Bachelor’s degree in Statistics, Mathematics, Physics, or another quantitative field, or equivalent practical experience.
5+ years of industry experience solving data science problems, or a quantitative PhD with 3+ years of industry experience.
Expertise applying advanced statistical methods and familiarity with machine learning systems and models.
Strong knowledge of optimization, statistical modeling, or time-series analysis.
Experience with Python, SQL, and R data-analysis libraries and packages.
Ability to work on site in Mountain View, California, United States.
Nice to have
PhD or Master’s degree in a quantitative field.
Experience in capacity engineering or infrastructure optimization at scale.
Familiarity with ML-driven forecasting and optimization techniques.
Experience with financial modeling, infrastructure cost-benefit analysis, automation tools for resource management, or quota allocation.
Knowledge of simulation workloads or high-performance computing environments.
Culture & Benefits
Work within the CORPIO team at the intersection of quantitative modeling, infrastructure automation, and simulation engineering.
Contribute to autonomous driving systems through large-scale simulation infrastructure optimization.
Eligibility for a discretionary annual bonus program and equity incentive plan.
Company benefits are available subject to eligibility requirements.
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