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Daily Productive Sharing 434 - How to Be A Successful ML Engineer?

Daily Productive Sharing 434 - How to Be A Successful ML Engineer?
Photo by Hunter Harritt / Unsplash

One helpful tip per day:)

(下附中文版)

#work #finance

Patrick Halina returned to her alma mater, the University of Toronto, to present advice on how to get a position as a machine learning engineer, and following are her key points.

  1. the best route to a machine learning engineer position is to do a relevant master's degree and then go for a position with a large company.
  2. go to a larger company because.
  3. there are more experienced engineers.
  4. more and bigger projects.
  5. don't worry about the salary in the first job, this is just the starting point and you can get a higher salary in later jobs.
  6. that an engineer with five years' experience and a master's degree may have more experience than an engineer with a PhD.

My personal experience is basically the same, it is very important to have an experienced mentor to help you grow, looking back on my experience, the two best mentors were one who worked at Douban for many years before and one who worked at Microsoft for many years.

And the other benefit of a big company is that there is a complete pipeline, where you can see how a machine learning model is done from development to launch and then iteration. This is basically impossible in a small company. Also, as a machine learning engineer, don't go to a consulting firm, you won't learn the full pipeline and you won't gain experience.

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Patrick Halina 回到母校多伦多大学介绍了如何获得机器学习工程师职位的建议,这是她的要点:

  1. 获得机器学习工程师职位最好的路径是读一个相关的硕士学位,然后去找大公司的职位;
  2. 去大公司是因为:
  3. 有更多经验丰富的工程师;
  4. 更多更大的项目;
  5. 第一份工作不需要过分考虑薪水,这份只是起点,你在后面的工作中可以获得更高的薪水;
  6. 一个有五年经验和硕士学位的工程师可能比一个博士学位的工程师更有经验;

我个人的体验也基本如此,有一个经验丰富的 mentor 带你成长非常重要,回顾我的经历,最好的两个 mentor 一位之前在豆瓣工作多年,一位在微软工作多年。而且大公司的好处是有完整的流水线,可以看到一个机器学习模型从开发到上线,再到迭代是如何完成的。这在小公司基本是不可能的。另外,作为机器学习工程师,千万不要去咨询公司,学不到完整的知识,而且积攒不了经验。

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