Топовая роль в крупном продуктовом сервисе с впечатляющей зарплатой и современным ML-стеком. Вариант для настоящего профи в распределенных системах с огромным влиянием на продукт.
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Высокая зарплатаСовременный стекТрендовый доменЧеткий скоупОтличные бенефиты
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Hirify AI/Оригинал
TL;DR
Senior Staff Machine Learning Systems Engineer (Ads ML Platform): Building infrastructure and workflow automation for the end-to-end Ads ML engineering lifecycle with an accent on feature development, training data, offline experimentation, and production reliability. Focus on designing distributed batch and streaming systems, ensuring data lineage and online/offline consistency, and extending platform capabilities into serving and online experimentation.
Location: Remote - United States
Salary: $292,500–$409,500 USD base salary per year, plus potential equity and commission depending on the position offered.
Company
Reddit operates a large-scale community platform with more than 100,000 active communities and approximately 130 million daily active unique visitors.
What you will do
Own the technical strategy for the end-to-end Ads ML engineering lifecycle, beginning with feature development, training data, offline experimentation, and model iteration.
Define architecture and technical standards for batch and streaming computation, backfills, data lineage, quality, observability, and online/offline consistency.
Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service.
Extend the platform strategy into model serving and online experimentation workflows.
Partner with Ads, ML Platform, Data Platform, modeling, product, and engineering teams to drive execution and clarify ownership.
Mentor Staff and senior engineers while raising architecture and operational standards.
Requirements
8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems.
4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.
Experience leading broad, ambiguous, multi-team platform initiatives from strategy through adoption.
Experience building platforms used by ML engineers, data scientists, or product teams developing production ML systems.
Deep experience with ML platforms, feature platforms, training data, experimentation, developer infrastructure, or distributed data infrastructure.
Experience with technologies such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, or Databricks.
Culture & Benefits
Flexible workforce with remote work available in countries where Reddit has a physical presence.
Comprehensive healthcare benefits and income replacement programs.
401(k) with employer match and global benefit programs.
Flexible vacation, paid volunteer time off, and generous paid parental leave.
Family planning support, gender-affirming care, and mental health and coaching benefits.
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