Machine learning is a subset of artificial intelligence based on the idea that computer systems can be programmed to learn from data and improve themselves without the need for human intervention. It is a complex field that combines several different disciplines, and it is one of the best tech jobs in 2021.
To become a professional in machine learning, you need proficiency in applied mathematics and physics, as well as hands-on experience in data modeling, natural language processing, and programming. In this guide, you’ll learn everything you need to get a job in machine learning.
What Is Machine Learning?
Machine learning is a method of data analysis and modeling. It enables computer systems to assimilate and process data, imitate human learning patterns, and improve their accuracy and decision-making without the need for extensive human interference. Machine learning projects can include a vector machine and a gradient descent model.
A machine learning engineer is a computer and information technology professional who designs and builds artificial intelligence systems and algorithms that can learn and make predictions without requiring further programming. Although this is the main career under the machine learning umbrella, there are other options as well.
Machine Learning Job Outlook
The Bureau of Labour Statistics doesn’t have data specific to machine learning. Instead, this career path is grouped under the category of computer and information research scientists. The job outlook for research scientists is 22 percent between 2020 and 2030, which is much faster than average.
What Education Do I Need to Become A Machine Learning Engineer?
To become a machine learning engineer, you need to have advanced knowledge of data science and deep learning. Ideally, you can earn a Bachelor’s Degree in Computer Science or some other form of professional training in the field. You can even improve this foundation by pursuing a master’s degree specializing in machine learning.
Can I Get a Machine Learning Job Without a Degree?
Yes, it is possible to get a job in machine learning without a degree. Because of the complexities of this field, professionals in machine learning usually aim for a master’s degree or at least a bachelor’s degree. However, thanks to new alternative education pathways, you can secure a job in this field through a coding bootcamp or professional certification.
Can a Coding Bootcamp Help Me Get a Job in Machine Learning?
Yes, it can. Coding bootcamps specialize in training students through accelerated learning programs, helping them master advanced technologies in programming and software design. Through their data science and analytics courses, you can easily gain the necessary coding skills to thrive in machine learning.
81% of participants stated they felt more confident about their tech job prospects after attending a bootcamp. Get matched to a bootcamp today.
The average bootcamp grad spent less than six months in career transition, from starting a bootcamp to finding their first job.
There are a variety of machine learning coding bootcamps to choose from that offer online, full-time, part-time, and self-paced options to aspiring students. Bootcamps also offer financing options to help you get started. They can also help you secure a job once you’ve finished the program.
How Long Does It Take to Get a Job in Machine Learning?
Typically, you should be able to secure a job within three months of completing a machine learning program because of how in-demand this field is. But first, you need to gain the necessary skills and experience. A bootcamp is the fastest route, and it can take you between three to six months to gain the necessary knowledge to break into this field.
You can also opt for a degree program. An associate degree from a community college takes two years to complete, while a bachelor’s degree typically takes four years to complete. You can also deepen your expertise through a master’s program, which takes an additional two years to complete.
Common Machine Learning Education Paths
A career in machine learning will provide you with a lot of benefits, including high salaries and innovative projects. We’ve compiled a list of common machine learning education paths to get you started right away.
Machine Learning Bootcamps
Machine learning bootcamps allow students to master the complex and advanced technologies necessary to succeed in machine learning within a short time. They offer flexible learning, financing options, and career support to help you secure a job. You get to learn online and from the comfort of your home or on campus amidst other technology enthusiasts.
Community colleges offer certificates as well as programs in machine learning as part of your computer science associate degree. The best part about this pathway is its affordability and learning format. You can either spend two years in an associate program or a few months acquiring a certificate.
Machine Learning Degrees
You can opt for a traditional Bachelor’s Degree in Computer Science or Information Technology, which will take you an average of four years to complete. Afterward, you can further specialize in machine learning through a master’s degree program. Master’s Degrees in Machine Learning usually take two years.
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Key Machine Learning Skills to List on Your Resume
To build a successful career in machine learning, you’ll have to master a few key skills. We’ve compiled a list of the most important skills to list on your resume so you can stand out from the crowd and secure that interview.
The complex computations and algorithmic tasks performed in machine learning and artificial intelligence are based on applied mathematical models. Results from these computations are often applied to solve practical problems. Expert knowledge of applied mathematics will give you an edge in your field.
Neural Network Architecture
Neural network architecture is an essential skill in machine learning because neural networks are the building blocks of deep learning algorithms. Machine learning engineers use this skill to imitate the biological neural network of animals and humans, and apply this to the design of software applications and computer systems.
Object Oriented Programming
Where to Find Machine Learning Jobs
There is a wide range of platforms where you can find machine learning jobs. These include job boards in your area and generalized online job search sites. However, to optimize the quality of your job search, you can use these specialized sites for machine learning and tech jobs.
ML Conf Job Board
The ML Conf job board is dedicated to helping machine learning professionals secure jobs. Employers can post openings for free. This board is regularly updated with vacancies in machine learning and software engineering roles. If you have analytical skills and relevant experience, you should try this job board.
The Dice job board provides tech professionals with a host of current job vacancies to choose from, including roles in machine learning. It also offers a wide range of career services specifically for tech professionals so they can thrive in the tech industry. This is a good place to look for jobs, no matter your academic background.
Harnham specializes in providing job seekers with vacancies in machine learning, deep learning, and artificial intelligence in companies across the country. This job site also offers career resources to job seekers in this field to enable them to stay updated and informed about the latest developments in the industry.
How to Prepare for Your Machine Learning Interview
To prepare for a machine learning role, you need to stay up to date on the latest trends and advances in the field. You should also research the company you want to work for and understand its goals and values. Below are some common questions you might encounter when applying for jobs in this field.
Machine Learning Interview Questions
- How do you set up a machine learning system?
- What are mode debugging and testing?
- What is feature engineering?
- What are the different types of machine learning algorithms?
The Five Highest-Paying Machine Learning Jobs
|Machine Learning Jobs||Average Salary||Projected Growth|
|Machine Learning Engineer||$140,210||74% annual growth|
|Data Engineer||$124,518||33% annual growth|
|Data Scientist||$119,211||37% annual growth|
|Full Stack Engineer||$105,926||35% annual growth|
|Robotic Engineer||$90,183||40% annual growth|
Job growth source: LinkedIn Emerging jobs report 2020
Machine Learning Engineer
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Machine learning engineers design and build self-directed artificial intelligence systems using data models and algorithms. Based on the 74 percent job growth for artificial intelligence and machine learning, according to the 2020 report by LinkedIn, there will always be a demand for machine learning engineers.
Data engineers conduct complex computations and research to find trends in datasets and develop algorithms to make data more valuable to users. This is a lucrative career in artificial intelligence that has a 33 percent annual growth rate.
Data scientists use scientific methods, processes, and algorithms to conduct data research. Their role is to process complex data so the results can be applied by users to solve practical problems or make decisions. This field has a long-term relevance based on the annual 37 percent growth report by LinkedIn.
Full Stack Engineer
Full stack engineers are professionals skilled in both front end and backend technologies to write programs and design websites. These IT professionals will always remain relevant in the tech industry based on their 35 percent annual growth.
Robotics engineers create and maintain robots and robotic systems that aid humans in performing tasks. You can become a robotics engineer as part of your machine learning career. Robotic engineers have an impressive annual growth of 40 percent, which means this field will produce many jobs in the future.
Machine Learning Career Path
There are many paths you can take to build your career in machine learning. Once you get your education, there are dozens of different jobs under the machine learning umbrella. We’ve compiled some of the main ones to help you create a roadmap and identify your goals.
Entry-Level Machine Learning Jobs
- Junior Data Scientist – These are recent graduates of data science programs with less than three years of experience. They have proficiency in maths and statistics, cloud technologies, and backend programming languages.
- Junior Machine Learning Engineer – These entry-level professionals have sufficient knowledge in programming, deep learning, applied mathematics, and data modeling.
- Business Intelligence Developer – Business intelligence developers have technical skills in the use of coding languages, data mining, and data analysis.
Mid-Level Machine Learning Jobs
- Associate Data Scientist – These are professionals with five years of experience in the field of data science. They are competent in data modeling, cloud administration, and backend technologies.
- Mid-Level Machine Learning Engineer – These professionals have at least five years of hands-on experience in the field of machine learning. They have skills in deep learning, natural language processing, and Python.
- Business Intelligence Analyst – These professionals have three to five years of experience in business intelligence and analytics, Tableau, data visualization, and database management.
Senior-Level Machine Learning Jobs
- Data Science Architect – These experts have at least six to eight years of experience and can hold managerial roles in this field. They have advanced skills in Python, Pandas, AWS Cloud, and Tableau.
- Senior-Level Machine Learning Engineer – These experts have five years or more of experience in A/B testing implementation, natural language processing, Python, TensorFlow, and networking models.
- Business Intelligence Manager – These professionals manage teams of business intelligence analysts and developers. They also lead strategic designs and maintain business intelligence applications.
Machine Learning Certifications
A professional certification in machine learning can help you demonstrate your specialized skills in this field. We have compiled a list of professional certifications offered by leaders in the tech industry to keep you on the right track.
The professional machine learning engineer exam assesses your ability to frame ML problems, architect ML solutions, and design data preparation and processing systems. You should also know how to develop ML models, automate and orchestrate ML pipelines, and monitor, optimize, and maintain ML solutions.
This certification guarantees that the holder is skilled in major areas in machine learning, such as supervised and unsupervised learning, deep learning, and reinforcement learning. This certification exam also tests your ability in time series analysis and survival analysis.
This certification was designed to equip professionals in development and data science roles with the technical knowledge required to build, train, tune, and deploy machine learning models using the AWS Cloud to solve practical problems.
Tips on How to Get a Job in Machine Learning
To get a job in machine learning, you need to implement effective preparation strategies. A job in machine learning can lead to a worthwhile career, but you have to go about it the right way. We have compiled the steps you can take to secure your dream job.
Research Machine Learning as a Field
You should understand what makes machine learning distinct before you venture into it. Make sure you learn about salary structure, career pathways, and job outlook, and understand what skills you need to cultivate to succeed in this growing field.
Enroll in a Formal Education Program
The next stage will be to enroll in a program. You can opt for a more traditional degree program or look for certifications to help demonstrate you have what it takes. Coding bootcamps are an excellent option because they are time and cost-effective and will equip you with the know-how to break into the field.
Practice with Mock Interviews
Mock interviews give you an insight into what you can expect from a real interview. They help you groom your technical, behavioral, and general knowledge of machine learning. Aside from practicing interview questions, you can join machine learning communities and network with actual professionals in the field.
Apply to Your Dream Job
If you’ve done all of the above, sum up the courage and apply for a machine learning position. Target job boards that specialize in advertising machine learning engineer positions. This increases your chances of securing a job in this field.
Should You Get a Job in Machine Learning in 2021?
Yes, you should try for a machine learning job in 2021. There is no time like the present to begin your journey in this growing and exciting field. If you’re passionate about developing new technologies and artificial intelligence, this field can transform your life.
It doesn’t hurt that machine learning has an average salary of $140,210 and a 74 percent annual growth, as explored above. Getting into this field isn’t difficult, either. With a little determination and three to six months in a coding bootcamp, you can begin your career in machine learning or any related field.
Machine Learning FAQ
Yes, you can. Aside from the traditional educational pathways, there are coding bootcamps and professional training and certification programs in this field that will equip you with the practical skills you need to get started.
No, it isn’t. There are lots of job vacancies in this field, and the majority of them offer you the opportunity to work from home. Several educational pathways are beginner-friendly to help you easily immerse yourself into the field.
Machine learning is applied in designing artificial intelligence software applications and systems to deliver an optimal experience to users. These applications and systems can self-direct and self-improve by imitating human thought processes. Examples include Siri, Alexa, self-driving cars, and chatbots, to name a few.
The top programming languages used in machine learning include Python, R programming, Java, and C++. Some of the software used in machine learning include TensorFlow, PyTorch, and Keras.
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