This includes topics such as linear regression, logistic regression, decision trees, and support vector machines.
Learn a programming language
Python is the most popular language for machine learning, but other languages such as R and Java are also used.
Build a machine learning portfolio
This will demonstrate your skills to potential employers. You can build a portfolio by working on personal projects or by contributing to open source projects.
There are a number of machine learning certifications available, such as the Google Cloud Certified Machine Learning Engineer Associate certification and the AWS Certified Machine Learning - Specialty certification.
Network with other machine learning engineers
This is a great way to learn about new opportunities and to get advice from experienced engineers. You can network online or at meetups and conferences.
Apply for jobs
Once you have the skills and experience, you can start applying for machine learning jobs. Be sure to tailor your resume and cover letter to each job you apply for.
Don't give up
The job market for machine learning engineers is competitive, but don't give up. Keep learning and growing your skills, and eventually you will find the right job.