问HN：学习机器学习推理基础设施的最佳实践路径是什么？
我是一名拥有超过8年经验的后端工程师。我的大部分工作集中在API、分布式系统、流媒体/实时系统以及云基础设施上。
我正在尝试向机器学习推理基础设施转型：模型服务、批处理等。但根据我的经验，获得这类工作的面试机会一直比较困难。
对于在这个领域工作的人来说：什么样的项目或经验才能真正让你相信一名后端工程师已经准备好从事推理基础设施的工作呢？
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I'm a backend engineer with 8+ years of experience. Most of my work has been APIs, distributed systems, streaming/real-time systems and cloud-infra.<p>I'm trying to move towards ML inference infrastructure: model serving, batching, etc. but based on my experience, it has been difficult to get a callback for such jobs.<p>For people working in this area: what projects or experience would actually convince you that a backend engineer is ready to work on inference infra?