Чётко описанная техническая роль в заметной AI-компании, хотя сочетание инженерии данных и количественного анализа может означать широкий круг задач.
?Широкий круг задач
Современный стек
Сфера AI
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Текст:
Hirify AI/Оригинал
TL;DR
Analytics Engineer (X) (Python/SQL, Spark, Flink): Building scalable data pipelines, analytical infrastructure, and quantitative models for high-volume datasets and global-scale decision-making with an accent on experimentation, forecasting, and data quality. Focus on designing real-time data systems, conducting A/B tests and causal analysis, and optimizing low-latency processing and operational efficiency.
Location: Palo Alto, California, United States
Base salary: $140,000–$225,000 USD per year
Company
xAI is building Super Intelligence systems across supercomputing infrastructure, Grok models, and applications including X.
What you will do
Design, implement, and optimize end-to-end pipelines for high-volume data using Spark, Kafka, and/or Flink.
Develop quantitative models and statistical frameworks for experimentation, forecasting, and performance measurement.
Build data infrastructure that maintains quality, consistency, and accessibility for analytical workflows.
Translate business requirements into production-grade data systems and insights in collaboration with product engineering, product, and operations.
Conduct A/B tests, causal analysis, and performance evaluations to improve key metrics.
Implement monitoring, alerting, automation, and mentoring practices for scalable data engineering and quantitative problem-solving.
Requirements
Bachelor’s or master’s degree in computer science, statistics, applied mathematics, or another quantitative field.
2+ years of experience building production data pipelines and infrastructure at scale.
Experience with Python, SQL, and distributed computing frameworks such as Spark, Flink, or Hadoop.
Nice to have
Expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
Understanding of cloud services for data storage, processing, and orchestration.
Experience in consumer technology or social media.
Experience with real-time streaming systems and low-latency data processing.
Contributions to open-source data tools or publications on large-scale analytics systems.
Experience reducing operational costs or improving system efficiency through data optimizations.
Ability to combine engineering excellence with rigorous analytical approaches.
Culture & Benefits
Mission-critical systems support quantitative decision-making at global scale.
Equity and comprehensive medical, vision, and dental coverage.
401(k) retirement plan, short- and long-term disability insurance, life insurance, discounts, and other perks.
Equal opportunity employer.
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