What kind of jobs can I get with machine learning?

If you are seeking answers for similar machine learning career queries, your search has now come to an end.

Here you will get all the essential details to kickstart your machine learning career. So, keep an eye on every element here to know how to get a machine learning job.

Machine learning is one of the most anticipated technologies across the globe these days. With the market enhancement of this technology, there are many machine learning career options available for high school graduates.

According to a recent report by SEMrush, 97 million people will be required for jobs like machine learning and AI specialists, big data specialists, process automation specialists, etc., by 2025.

The demographic reflects a great scope for upcoming machine learning job seekers. So, let us move ahead to know how can you initiate your machine learning career with a summary of this intuitive guide:

  • Choose your desired machine learning job title to initialize your career
  • Understand the process of starting your career in machine learning
  • Strengthen your programming skills to perform better as an ML Engineer
  • Get all the educational degrees and certifications required as per your machine learning job title
  • Apply with a professional resume to grab a machine learning job in 2022

To apply for any job, even apart from machine learning, you will need a job-winning resume. And, Hiration can ease your professional resume building process with the help of its AI-powered Online Resume Builder.

In terms of machine learning career guidelines, we have answered the following fundamental questions:

Types of Machine Learning Jobs

People willing to opt for a machine learning career path usually get confused in choosing the right profile title.

Considering it as an important step of your professional journey, we are differentiating eight machine learning-based profile titles here.

You can choose any of these and acquire suitable machine learning skills to step into the machine learning career path:

  • Machine Learning Engineer

A machine learning engineer develops and manages machine learning algorithms for Artificial Intelligence-based projects.

  • Data Scientist

A data scientist collects, analyzes and interprets complex data sets with the help of machine learning algorithms and data analytics.

  • Natural Language Processing Scientist

A natural language processing scientist works to bridge the gap between human language and computer understanding.

  • AIOps Engineer

An AIOps (Artificial Intelligence for IT Operations) engineer develops and deploys machine learning algorithms to analyze IT data and boost productivity.

  • Business Intelligence Developer

A business intelligence developer analyzes data sets based on business and the latest market trends.

  • Computational Linguist

A computational linguist builds and uses machine learning algorithms to teach computers about human language understanding.

  • Cloud Architect for ML

A cloud architect in a machine learning company stores and manages huge amounts of machine learning data in the cloud.

  • Deep Learning Engineer

A deep learning engineer develops and deploys deep learning algorithms to build a human-centered AI system.

  • Robotics Engineer

A robotics engineer designs & builds robots and complex robotics systems with the help of machine learning.

Also Read: Machine Learning Jobs

How to Start a Career in Machine Learning?

Young machine learning admirers hustle the most with this or similar questions. To make the transition easily understandable, here we have divided our machine learning career approach into three divisions:

The Introduction Phase

The first step of becoming a machine learning engineer is to clear all the misconceptions about machine learning technology because of borrowed opinions and half-baked information.

To get the fundamental machine learning knowledge, you can try reading books like:

  • Programming Collective Intelligence by Toby Segaran
  • Machine Learning by Tom M. Mitchell

Moreover, reading AI and machine learning blogs will keep you updated with the latest trends. Here are some blogs that you can consider following:

The Learning Phase

As the second step of getting a machine learning engineer job, you must acquire practical machine learning skills.

Here we have listed the two most essential machine learning skills that will help you bag entry level machine learning jobs:

  • Statistics (Especially Bayesian Probability)
  • Programming Skills (R or Python)

The Application Phase

Finally, it would be best to build a portfolio of some machine learning projects you have worked upon to showcase your expertise with the technology.

Many certification courses allow you to work on a live machine learning project that can be added to your portfolio. However, some courses do not provide such a facility.

The bottom line is that you should have practical machine learning application knowledge and projects to grab a machine learning engineer job.

Essential Machine Learning Courses

You can find numerous machine learning courses available online, but not all of them will give you complete exposure to essential machine learning aspects.

To keep you up with the flow of advancements in machine learning, here we have listed the top 7 online machine learning courses that can add value to your machine learning career:

Must-Have Programming Skills For a Machine Learning Engineer

As a machine learning engineer, you will have to develop machine learning algorithms with the help of programming languages including Python, R, and C++. Hence, you need to be proficient in coding to initiate your machine learning career.

Furthermore, familiarity with Google's TensorFlow software library will also benefit entry-level machine learning engineers as it allows users to code in Java, Python, and C++.

For beginners, we also recommend PyTorch, a framework for machine learning developers to use with the imperative programming level. Additional programming languages suitable for machine learning engineer jobs are:

  • SQL
  • R
  • Java
  • Scala
  • Julia

Educational Qualifications Needed For a Machine Learning Engineer Job

To begin your machine learning career, you should have a bachelor’s degree in computer science, mathematics, statistics, or any similar subject.

Higher-level machine learning jobs require a Ph.D. or master’s degree in computer vision, machine learning, deep learning, neural networks, or any similar niche.

Apart from a conventional degree, many universities and online learning platforms provide certifications in artificial intelligence, machine learning, data science, etc. You can opt for such certifications as per the requirement of your targeted job profile.

Top Universities Offering Master's Degree Machine Learning Courses in the US

You can start your machine learning career with a bachelor's degree and an ML certificate. However, you will need a master's degree in machine learning if you want to bag a higher-level machine learning job in the future.

Considering this, we have listed some finest US universities offering master's degree machine learning courses in 2022:

  • Carnegie Mellon University | Pittsburgh, Pennsylvania
  • Cornell University | Ithaca, New York
  • Georgia Institute of Technology | Atlanta, Georgia
  • Duke University | Durham, North Carolina
  • Massachusetts Institute of Technology | Cambridge, Massachusetts
  • Boston University | Boston, Massachusetts
  • The University of Rochester | Rochester, New York
  • The University of California | San Diego, California
  • Stevens Institute of Technology | Hoboken, New Jersey
  • Stanford University | Stanford, California

Machine Learning Certifications to Boost Your Career

Technical machine learning certifications will boost your career exponentially. Here are some machine learning certificates that can make your profile shine in 2022:

Answering Top 7 Machine Learning Career Most Common Questions

Machine Learning is one of the most trending career options these days. Hence, it is important to clear all your doubts about the machine learning career option to experience a smooth professional journey.

Considering this, we have curated seven most asked machine learning career questions here:

Is machine learning a good career?

Machine learning is undoubtedly one of the best career choices for high school graduates. They can get a bachelor’s degree in computer science, mathematics, or statistics to start their machine learning career.

According to a recent report by OMDIA, the annual revenue of the AI software niche globally will reach up to USD 100 billion by 2025. The figures show that we will get numerous artificial intelligence and machine learning engineer job opportunities in the upcoming years.

How can I learn machine learning on my own?

Well, it depends on your current status. If you are a high school graduate, you can opt for a computer science or mathematical degree course.

But, if you are a college graduate, you need to put extra effort into it. Programming language is an essential part of machine learning. Hence, it will be great to learn Python first as it is easy to learn and use.

After that, you can read machine learning books and guides to push your learning process. Getting certified via an authentic online platform or community can also add great value to your machine learning career.

What are the skills required for a machine learning engineer job?

Pro-level analytical knowledge and intermediate programming skills can help you in getting machine learning entry level jobs.

Machine learning engineers use these skills to develop smart machine learning algorithms for complex AI systems.

The fundamental machine learning skills for getting a machine learning engineer job are:

  • Probability & Statistics
  • Programming languages like C++/Python/Java/R
  • Machine Learning Algorithms
  • Data Modeling & Evaluation
  • Distributed Computing
  • Advanced Signal Processing Techniques
  • Calculus
  • Linear Algebra

What are some algorithms that every machine learning engineer should know?

Machine learning algorithms are designed and developed to automate any process or solve any real-world problem with minimal human efforts.

As a machine learning engineer, you must have practical knowledge of the following algorithms:

  • Apriori Algorithm
  • Linear Regression
  • Artificial Neural Networks
  • Logistic Regression
  • K Means Clustering Algorithm
  • Decision Tree
  • Naive Bayes Classifier Algorithm
  • SVM Algorithm
  • Support Vector Machine Algorithm
  • KNN Algorithm
  • Random Forest Algorithm
  • Gradient Boosting Algorithm
  • Dimensionality Reduction Algorithms
  • AdaBoosting Algorithm

What are the top industries for machine learning jobs?

Machine learning is slowly affecting every industry beneath this sky. The human race is trying to make every machine smarter to minimize physical efforts.

According to a report by LinkedIn, these are the top 10 sectors influenced by machine learning in the world:

  1. Healthcare
  2. Transcription
  3. Financial Services
  4. Transportation
  5. Cybersecurity
  6. Manufacturing
  7. Marketing
  8. Software Development
  9. Trading
  10. Online Toxicity

What are the starting salaries of machine learning jobs?

The starting salary of a machine learning professional varies based on the job location and industry type. According to TechRepublic, the salary range of machine learning entry level jobs starts from nearly USD 90,000 and goes up to USD 200,000.

Moreover, here we have also curated average salary data of some machine learning job profiles via Indeed:

Profile Title Average Annual Salary
Machine Learning Engineer USD 141,214
Data Scientist USD 114,437
Business Intelligence Developer USD 94,376
Computational Linguist USD 109,434
Cloud Architect USD 133,906
Deep Learning Engineer USD 132,087
Robotics Engineer USD 89,662

Also Read Machine Learning Engineer Salary

What are some common machine learning interview questions?

To clear out the interview process of your applied machine learning engineer job, you must understand all the AI and ML concepts competently.

Here are some questions that the recruiter might ask during your interview round:

  • Explain the difference between Data Mining & Machine Learning.
  • What do you understand about cross-validation techniques?
  • Under what circumstances does a model exhibit poor performance?
  • Explain the functionality of unsupervised learning.
  • What are your strong algorithm techniques?
  • What do you mean by model selection?
  • Where do we use pattern recognition?
  • What are ICA, PCA, and KPCA?
  • What machine learning techniques do you use often and why?
  • What is assembly learning?

Read More: Machine Learning Interview Questions

Hiration Works as a Catalyst

After acquiring all the educational qualifications, certifications, and skills suitable for your machine learning job title, you will need an impactful Machine Learning Resume to apply for ML and deep learning jobs.

Hiration has built an Artificial Intelligence-powered Online Resume Builder to ease your machine learning resume building process. You can also check out Hiration’s additional professional tools here:

You can use our 24/7 chat support if you encounter any issues while operating these digital tools.

Key Takeaways

Take a look at the key takeaways of this reference guide:

  • Get all the fundamental machine learning knowledge with the help of suitable books and blogs
  • Learn programming languages and other skills suitable to your chosen machine learning engineer job title
  • Apply with a portfolio of some machine learning projects you have worked upon and a machine learning resume

These are some important details to initiate your machine learning career. You can easily get a machine learning engineer job by following the above-given guidelines.

We have tried to shed light upon every aspect that can help you become a Machine Learning Engineer. Still, if you need any machine learning career-oriented assistance, you can contact us at support@hiration.com.

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