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A lot of machine learning positions require a PhD, especially if you're going for big companies like Google. The most important thing though, as usual in the tech field, is demonstrating your expertize. You can do so in a number of ways:

  1. Work on your own projects and contribute to open source code.
  2. Get an internship if you can.
  3. Pick some data sets and do some interesting analysis on them.
  4. Join machine learning competitions like the ones from Kaggle.
  5. If you don't have a PhD but want to demonstrate PhD-level expertize, there's always the possibility of getting your papers published in peer-reviewed journals.

Also, it's also a good idea to attend machine learning workshops and events to network with professionals in the field.

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1. Develop a strong understanding of the fundamentals of machine learning, including the different algorithms and techniques used. 

2. Become proficient in programming languages related to machine learning, such as Python and R.

3. Familiarize yourself with the machine learning tools and frameworks commonly used in the US, such as scikit-learn, TensorFlow, PyTorch, and Keras.

4. Practice solving real-world machine learning problems using data sets and tools available online.

5. Work on developing your communication skills, as many machine learning jobs involve collaborating with other teams.

6. Brush up on your knowledge of the different job roles in machine learning and the skills required for each.

7. Network and make connections with professionals in the field.

8. Consider getting certified in machine learning to demonstrate your expertise and knowledge.
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To prepare for machine learning jobs in the USA, gain knowledge in statistics, programming, and ML algorithms. Build a strong portfolio, network, and stay updated on industry trends.
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The best way to prepare for machine learning jobs in the USA will vary depending on the individual's specific needs and abilities. However, some general tips that may help include studying for and taking practice exams for machine learning jobs in the USA; considering whether or not to purchase specific training materials; and targeting specific jobbery or training programs that can help you gain the skills necessary for the job.
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Work on your own projects and contribute to open source code.

Get an internship if you can.

Pick some data sets and do some interesting analysis on them.

Join machine learning competitions like the ones from Kaggle.

If you don't have a PhD but want to demonstrate PhD-level expertize, there's always the possibility of getting your papers published in peer-reviewed journals.
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To prepare for machine learning jobs in the USA, consider the following steps:

1. Gain a solid understanding of machine learning concepts and algorithms through coursework or online resources.

2. Develop practical skills by working on real-world projects and participating in Kaggle competitions.

3. Build a strong foundation in programming languages like Python and R.

4. Pursue higher education or certifications in machine learning or related fields.

5. Network with professionals in the industry and stay updated on the latest advancements in the field.
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