数据/人工智能/智能系统软件工程师
Software Engineer Data/AI/Intelligent Systems
Cisco 是一家专注于在人工智能时代革新数据和基础设施的领先科技公司。该职位涉及开发可扩展的数据管道，构建分析平台以支持机器学习计划，使 Cisco 的业务部门能够利用 AI 实现运营卓越性。
开发可扩展的数据管道
设计稳健的分析平台
构建支持机器学习计划的基础设施
以创新和注重细节的方式解决复杂挑战
构建和维护关键的软件工具和平台
要求
在过去 3 年内完成或当前正在就读并预计在 12 个月内完成认证或相关学位课程（例如：专科、学徒制、训练营或专业认证 + 1 年相关经验，高中文凭 + 2 年相关经验）或本科 + 0 年相关经验
熟练掌握 Python，对基本数据结构有深入理解
具备 TensorFlow、PyTorch 或 scikit-learn 等机器学习框架的实际操作经验
熟悉分布式数据处理技术，包括 Apache Spark、Hadoop（MapReduce）或 Apache Flink
具备使用容器化和编排工具（如 Docker 和 Kubernetes）部署数据和机器学习工作负载的经验
优先考虑
具备 AI/ML 实际操作经验
熟悉主要云平台，如 AWS、Azure 或 Google Cloud
了解分布式系统概念，包括可扩展性、可靠性、容错性和数据一致性，以及熟悉分布式计算模式（如负载均衡、共识算法和服务间通信）
最初发布于 喜马拉雅山
查看英文原文
Cisco is a leading technology company focused on revolutionizing data and infrastructure in the AI era. The role involves developing scalable data pipelines and building analytics platforms to support machine learning initiatives, enabling Ciscos business groups to leverage AI for operational excellence.
Develop scalable data pipelines
Design robust analytics platforms
Build infrastructure to support machine learning initiatives
Solve complex challenges with innovation and attention to detail
Build and maintain key software tools and platforms
Required
Completion within the past 3 years, or current enrollment with expected completion within 12 months, of a certification or relevant degree program (e.g., Associates, Apprenticeship, Boot Camp, or Certification in a specialized program + 1 year of relevant experience, High School Diploma + 2 years of relevant experience) or Bachelors + 0 years of relevant experience
Proficiency in Python, with a strong understanding of fundamental data structures
Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
Familiarity with distributed data processing technologies, including Apache Spark, Hadoop (MapReduce), or Apache Flink
Experience with containerization and orchestration tools, such as Docker and Kubernetes, for deploying data and machine learning workloads
Preferred
Hands-on experience with AI/ML
Familiarity with major cloud platforms, such as AWS, Azure, or Google Cloud
Understanding of distributed systems concepts, including scalability, reliability, fault tolerance, and data consistency, as well as familiarity with distributed computing patterns (e.g., load balancing, consensus algorithms, and inter-service communication)
Originally posted on Himalayas