Many people fear that robots and artificial intelligence (AI) systems are going to steal their jobs. To a certain degree, those fears are warranted. According to data from the McKinsey Global Institute, as many as 73 million U.S. jobs could be automated by 2030.

许多人担心机器人和人工智能(AI)系统会抢走他们的工作。 在某种程度上， 这些恐惧是有根据的 。 麦肯锡全球研究所的数据显示，到 2030年，美国将有7300万个工作岗位实现自动化。

While that’s concerning at a surface level, many people ignore the fact that automation is actually a good thing. It keeps workers out of harmful environments, speeds up production lines, and paves the way for better overall opportunities. Just because robots and AI take over certain jobs doesn’t mean that there won’t be other ones available.

尽管这是表面上的问题，但许多人忽略了自动化实际上是一件好事的事实。 它使工人远离有害环境，加快了生产线，并为获得更好的总体机会铺平了道路。 仅仅因为机器人和AI接管了某些工作，并不意味着就没有其他工作了。

Still, the idea of losing your job to a robot is frightening. That’s why many people are looking for a future-proof position. According to that logic, there’s no better job field to enter than that of artificial intelligence. Even if machines take over countless jobs, humans are still necessary to program the algorithms.

尽管如此，丢掉工作给机器人的想法还是令人恐惧的。 因此，许多人都在寻找适合未来发展的职位。 根据这种逻辑，没有比人工智能更好的工作领域了。 即使机器接管了无数的工作，仍然需要人工来对算法进行编程。

Moreover, jobs in the AI field pay top dollar as companies look for the brightest minds to create tomorrow’s solutions. Whether you’re just getting ready to start your career or are reskilling into a new position, these five AI jobs are the best out there. Here’s how you can get hired into them.

此外，随着公司寻找最有才华的人才来创造明天的解决方案，人工智能领域的工作收入最高。 无论您是准备开始自己的职业生涯，还是要重新晋升为新职位，这五个AI职位都是最好的。 这就是您如何被雇用的方法。

机器学习工程师 (Machine Learning Engineer)

At its core, artificial intelligence relies on a technology known as machine learning. It involves carefully crafted algorithms and software platforms that enable the AI to do its job. Of course, those need to be created by someone.

人工智能的核心依赖于称为机器学习的技术。 它涉及精心打造的算法和软件平台，使AI能够完成其工作。 当然，这些需要由某人创建。

Machine learning engineers are up to the task-and rake in a median salary of $114,000 for their efforts. They are primarily responsible for building and managing these platforms. Those with a background in data science and who are fluent in multiple programming languages are ideal candidates for the role.

机器学习工程师要完成任务，他们的工作中位数收入为114,000美元 。 他们主要负责构建和管理这些平台。 具有数据科学背景并且精通多种编程语言的人员是该职位的理想人选。

A machine learning engineer can expect to work with predictive models, natural language processing, massive datasets, and a variety of other development tools. In terms of education, most companies look for someone with a master’s or doctoral degree in mathematics or computer science.

机器学习工程师可以期望使用预测模型，自然语言处理，海量数据集以及各种其他开发工具。 在教育方面，大多数公司都在寻找具有数学或计算机科学硕士学位或博士学位的人。

For individuals without those academic credentials, a position as a regular software developer is a great starting place. This not only lets you gain the programming skills needed, but it also opens the door for valuable experiences with problem-solving and analytical skills.

对于没有这些学历的个人， 常规软件开发人员的职位是一个很好的起点。 这不仅使您获得了所需的编程技能，而且还为解决问题和分析技能的宝贵经验打开了大门。

数据科学家/工程师 (Data Scientist / Engineer)

Anyone familiar with the field of artificial intelligence knows that data trumps all. It is at the heart of every algorithm and application. As such, individuals who know how to work with data are in high demand. Data science is a broad field, but it is closely intertwined with the AI sector due to the similarities between the two.

任何熟悉人工智能领域的人都知道数据胜过一切。 它是每个算法和应用程序的核心。 因此，迫切需要知道如何处理数据的个人。 数据科学是一个广阔的领域，但是由于两者之间的相似性，它与AI领域紧密相关。

Those working as data scientists can expect to earn a median salary of $113,000 per year. However, the positions can’t be filled by just anyone. Companies expect that data scientists hold a master’s or doctoral degree in computer science.

那些从事数据科学家工作的人的平均年薪为113,000美元。 但是，职位不能仅由任何人填补。 公司期望数据科学家拥有计算机科学的硕士学位或博士学位。

It’s worth noting that being a data scientist could be perfect for someone that isn’t as interested in programming from scratch. Individuals in data science roles typically work with Big Data tools like Hive, Hadoop, MapReduce, Pig, and Spark. However, that doesn’t mean that programming isn’t part of the job. In-depth knowledge of languages like Perl, Python, Scala, and SQL is also necessary.

值得注意的是，对于那些对从头开始编程不那么感兴趣的人，成为数据科学家可能是完美的选择。 担任数据科学职务的人员通常会使用诸如Hive，Hadoop，MapReduce，Pig和Spark等大数据工具。 但是，这并不意味着编程不是工作的一部分。 还需要深入了解Perl，Python，Scala和SQL等语言。

Given the demanding requirements of the job of a data scientist, most people don’t land a position immediately out of school. Those with a multi-year background in a related position are often considered first.

考虑到数据科学家工作的苛刻要求，大多数人不会立即离开学校。 那些具有多年相关职位背景的人通常被优先考虑。

人工智能研究科学家 (Artificial Intelligence Research Scientist)

There can be no advances made in the field of AI without research. As such, AI research scientists are in high demand. Individuals aspiring to fill one of these roles can expect to make a median salary of $77,000 per year. Though that isn’t as lucrative as the two positions mentioned previously, the research world is full of ways to make money.

没有研究，就不可能在AI领域取得进步。 因此，对AI研究科学家的需求很高。 有志担任这些职位的人的平均年薪为$ 77,000。 尽管这没有前面提到的两个职位有利可图，但研究界充满了赚钱的方法。

For instance, a major breakthrough could be worth millions. Likewise, those daring enough to create an AI research firm of their own could be bought out or absorbed into a larger company for millions or even billions of dollars.

例如，一项重大突破可能价值数百万美元。 同样，那些敢于创建自己的AI研究公司的公司可能会被收购，或者以数百万甚至数十亿美元的价格被更大的公司吸收 。

AI research scientists need to have expert knowledge of multiple AI disciplines. These include areas like applied mathematics, machine learning, deep learning, and computational statistics. While an advanced degree is typically favorable, many research institutions and companies also value experience in a related field.

AI研究科学家需要具有多个AI学科的专家知识。 这些领域包括应用数学，机器学习，深度学习和计算统计。 通常，高级学位是有利的，但许多研究机构和公司也重视相关领域的经验。

自然语言处理 (Natural Language Processing)

Although AI has uses in almost every industry, most consumer-facing products revolve around language. These include everything from chatbots to virtual assistants to video games. Obviously, computers don’t communicate like humans. However, artificial intelligence can bridge the gap between the two with natural language processing. It involves the use of machine learning to teach computers to understand and speak like humans.

尽管AI几乎在每个行业中都有使用，但大多数面向消费者的产品都是围绕语言展开的。 其中包括从聊天机器人到虚拟助手再到视频游戏的所有内容 。 显然，计算机不会像人类那样进行通信。 但是，人工智能可以通过自然语言处理弥合两者之间的鸿沟。 它涉及使用机器学习来教计算机像人类一样理解和说话。

It’s also a growing field. Individuals with the skills to land a job in natural language processing should expect annual salaries of around $107,000. An advanced degree in computer science is preferable. Most individuals also seek out additional qualifications specifically related to linguistics and human-computer interfaces.

这也是一个不断发展的领域。 具有在自然语言处理中找到工作的技能的个人应期望的年薪约为107,000美元 。 具有计算机科学高级学位者优先。 大多数人还寻求与语言学和人机界面特别相关的其他资格。

商业智能工程师 (Business Intelligence Engineer)

While being a software engineer is the “sexy” side of computer science, there is also remarkable demand for the less glamorous side. Business intelligence engineers use AI to analyze complex data to identify business trends. These individuals play a key role in helping companies increase their profit margins and efficiency.

尽管成为软件工程师是计算机科学的“性感”方面，但对于不那么迷人的方面也存在着巨大的需求。 商业智能工程师使用AI分析复杂数据以识别业务趋势。 这些人在帮助公司提高利润率和效率方面发挥着关键作用。

Business intelligence engineering jobs typically have a median salary of $81,000. Those interested in pursuing such a position should have strong analytical skills. They also need to be able to communicate effectively with colleagues who don’t come from a technical or computer-based background.

商业智能工程工作的平均年薪为81,000美元 。 那些有兴趣担任这样职位的人应该具有较强的分析能力。 他们还需要能够与并非来自技术或计算机背景的同事进行有效的沟通。

Notably, business intelligence engineers don’t often need an advanced degree. Having a bachelor’s degree is typically enough. However, on-the-job experience and certifications are desirable.

值得注意的是，商务智能工程师通常不需要高级学位。 具有学士学位通常就足够了。 但是，需要在职经验和认证。

As AI continues to branch out into new industries, jobs in this area will become even more plentiful. Those who are able to land a position now will be well-positioned to become industry experts by the end of the decade.

随着AI继续涉足新行业，该领域的工作将变得更加丰富。 那些能够找到职位的人将在本世纪末成为处于行业专家的有利条件。

Originally published at https://www.theburnin on June 8, 2020.

最初于 2020年6月8日 在 https://www.theburnin 上 发布 。