Machine Learning Engineering is an IT role concerned with deep learning. It is projected to continue its rise in popularity as more industries begin to understand the value of investing in deep learning technologies, which is seen particularly in media, healthcare and manufacturing sectors. These engineers are adept at creating technologies embedded with AI, artificial intelligence, which allows the machine to complete an intended task without being prompted to do so. Common examples of what Machine Learning Engineers work on include self-driving cars for Uber and programming tailore...more
See results by role, experience, and location.
Data is from real (not self-reported) interviews and offers on Hired.
We've got salaries for other top technical roles, too.Explore Salaries
The job prospects and compensations for Machine Learning Engineers varies across cities. See where Machine Learning Engineers are the most sought after.
Whether you're looking for a new job or want to land your next
promotion, salary negotiation is a critical career skill.
Our complete Salary Negotiation Guide will make sure you're prepared
to land the salary you deserve, articulate your skills, and common
mistakes to avoid during the interview process.
We've collected tons of information on salaries, compensation, negotiation and more. See even more on our blog.
We are designers. We are Those Who Solve Problems with Interfaces. We are the ones who would take a solid flowchart, wireframe, or screen over any amount of explanation with… words (no, the irony of that sentiment in an article for designers is not lost on me)! So let me present a new problem statement for […]
When we talk about UX Design careers, working from home in comfy pajamas isn’t the first thing that comes to mind. The common perception of a UX Designer is someone embedded in the product team, juggling in-office workshops and face-to-face stakeholder meetings. It’s true that in-person contact has been key to delivering UX work since […]
Are you an engineer or developer who practices that two-for-one life hack of learning new skills by taking on a side project? It may be time for you to take that side-project and turn it into a business! Whether your goal is to generate side income with a humble app or become a millionaire through […]
Part resume, part advertisement, design portfolios are the universal adapter of the hiring process. They not only showcase previous design deliverables and specialty projects, but also illustrate the designer’s sensibilities, experiences, and specialized skills. Your portfolio provides hiring managers, interviewers, and collaborative team members with a visual and functional frame of reference for your working […]
Like any good design challenge, successfully “designing” the UX/UI interview requires a carefully applied combination of user empathy, communication strategy, and emphasis on skill. For professional UX/UI designers, this is exactly the type of challenge they tend to rise to. Here are three important skills to demonstrate in your UX/UI interview. 1.User Empathy Different teams […]
With coding bootcamp as a viable option for those who want to become software developers, it’s never been a better time to consider exactly how you want to map out your education. The biggest factor in making the decision between bootcamp or full undergrad degree is lifestyle. In many ways, they are opposite in their […]
To stay competitive in a tough market, career driven developers know that they should always be learning new things. If you’re determined to accelerate your career, boost your portfolio, or take your own side-project to the next level, animation is where it’s at! Many of us, especially those of us who work at companies with […]
Agile is not just a buzzword. Being agile is everything I do and live for as a PM. In this fast moving and uber-competitive industry, agility is how you stay ahead of market expectations and keep customers happy. But being agile is not about shipping new products and features quickly. Being agile is about learning quickly. […]
Many of us know how tough it can be to miss out on a promotion—particularly when your colleagues are celebrating their own successes from a recent round of performance reviews. So when you manage a team or an individual for the first time, it can be tough to break the news that they didn’t get […]
Answer a few questions to complete your profile.
Companies request interviews with upfront compensation.
Find your dream job!
Machine Learning Engineering is an IT role concerned with deep learning. It is projected to continue its rise in popularity as more industries begin to understand the value of investing in deep learning technologies, which is seen particularly in media, healthcare and manufacturing sectors. These engineers are adept at creating technologies embedded with AI, artificial intelligence, which allows the machine to complete an intended task without being prompted to do so. Common examples of what Machine Learning Engineers work on include self-driving cars for Uber and programming tailored search results for Google users. Machine Learning utilizes the most cutting-edge technology, so professionals in this field must have the desire to seek and master new technologies as they emerge.
An entry-level Machine Learning Engineer will design and build models, often on a team, that follow data science and AI technologies. They will be expected to understand the needs of the business and conceptualize projects that meet business goals. Being tech savvy and having a desire to create automated technologies that make life easier should always be the goal of a Machine Learning Engineer, particularly when new to the field.
Most Machine Learning Engineering professionals have an advanced degree in computer science, an engineering discipline or statistics. Some employers may prefer their Machine Learning Engineers to keep an updated engineering license. The type of education and skills a potential employer may keep in mind when considering hiring an entry-level Machine Learning Engineer can include:
Machine Learning Engineer work is highly sophisticated, so professionals in this field need a high level of education and technical experience to advance their career. In most cases, a bachelor’s degree is not enough and many employers expect Machine Learning Engineer candidates to have a master’s or Ph.D. in computer science, an engineering discipline, or mathematics.
Experience is also key to becoming a successful Machine Learning Engineer. These engineers gain experience by working on practical and theoretical models to enhance and demonstrate their hands-on skills. This is a field like many other scientific and technical roles, as there is plenty of trial and error.
Machine Learning Engineers at the junior level have demonstrated years of on-the-job experience, gaining expertise on the machine and deep learning technologies through teamwork and project-specific experiments. At the junior level, a Machine Learning Engineer will be expected to take on more responsibilities, perhaps even leading a junior team and may often help with training new hires.
By demonstrating a consistent progression in your work, a skilled Machine Learning Engineer can easily work their way up the career ladder, from entry-level, to junior and into senior ranks. This may occur by being a great team player and working well on cross-functional teams. Following trends in technology and learning new skills will also signify to your employers how curious you are. The ability to take reasonable risks and try out an experiment and not being dismayed if it fails will show how determined the Machine Learning Engineer is.
An ascent up the Machine Learning Engineer career path takes fortitude, a desire to learn and being an excellent team player. With these skills in mind, there is every reason why moving up in the ranks should be possible.
Machine Learning Engineers at the senior level have developed a mastery for deep learning and data science, but they do not rest on their laurels. The key to attaining a Senior Machine Learning Engineer position is to keep challenging yourself to pick up new skills related to technology and AI. Employers will likely promote Machine Learning Engineers who not only have the technical skills earned through years of work but those who also consider their colleagues and the company at large. Having an interest in mentoring junior colleagues and being able to communicate effectively with team members about your work is what senior Machine Learning Engineers do well.
Reaching a senior level will pay off in many ways, not only financially, but in the respect, the Machine Learning Engineer will command and the type of interesting work they will be expected to spearhead.
The precise skills a Machine Learning Engineer may need may depend on the company they work for, though there are certain fields that all Machine Learning Engineers will likely need on the job. Computer programming skills are a must. A growing trend towards having an aptitude with Python, Java, C and C++ programming languages is also emerging. Studying where Machine Learning technology is being utilized, such as with self-aggregating newsfeeds and understanding the ins-and-outs of how this technology is created can help build basic AI skills. And finally, following deep learning trends in the industry can help Machine Learning Engineers understand the future of their careers.
Machine Learning Engineering is still a relatively new career but is quickly building traction as a field set to change the face of the world. Engineers in this field should strive to stay on top of emerging technologies and industry trends to stay relevant. This can be done by taking additional courses, either online or at a special technical school, as well as attend seminars and conferences, network and keep an eye out for literature pertaining to movements within the industry.
There are similar fields to Machine Learning, the understanding of which can make a Machine Learning Engineer an even stronger professional. Some of these roles include data and research scientists, computer vision engineers and business intelligence developers, all of whom study data patterns, set research experiments and create software and systems that help automate certain functions and make work and life easier. A Machine Learning Engineer who wants to keep their skills sharpened will take the time to study up on these professions and see what they can learn about the trial and error experienced in these roles.
Machine Learning Engineers create new systems and machines that are powered with artificial intelligence to complete assigned tasks without prompting. Companies with Machine Learning Engineers are seeing incredible investments rolling in for their projects, as deep learning machines and technologies are being sought and utilized in virtually every sector. Machine Learning Engineers can find excellent employment working for healthcare companies that want to make uncovering diseases in patients quicker and more precise; in manufacturing, as companies continue to automate work to increase production and reduce injuries; in media, helping news organizations attract more readers by learning what topics pique their interests and programming related feeds to entice them to click and so much more.
Deep learning and AI are considered by experts as the wave of the tech future, with Machine Learning Engineers taking the helm and creating incredible intelligent devices.
Machine Learning Engineers at the senior level can enjoy a long and fruitful career where they are, helping to develop and deploy intelligent systems that guide the future and affect the daily lives of millions of people.
For those interested in a career change may consider such roles as senior data scientists, product managers and DevOps managers, as they rely on the same research, trial and error and dedication at which Machine Learning Engineers excel.
There is every reason for senior Machine Learning Engineers to stay where they are since it is a career that experts agree is growing and evolving. Millions of Machine Learning Engineer jobs are predicted to open over the next decade or so as automation is seen as the way for businesses across all sectors to expand and improve their operations. Being there as new technologies take off is exceedingly rewarding and staying ahead of the curve is the secret to lasting success.
R is a language designed for data manipulation and visualization. It is capable of doing various statistical computing and graphic generation (including linear and nonlinear modelling, classical statistical tests, time-series analysis, classificat...
Python is an object-oriented programming language notable for its clarity, power and flexibility. Python is an interpreted language, meaning that an interpreter reads and runs the code directly, rather than compiling down into static lower level c...
Analytics and Business Intelligence roles are often confused but are also directly linked. Data that is collected when a user interacts with a system is then cleaned and stored. That data is then accessed using reports and graphical dashboards. Th...
Manufacturing involves creating merchandise through various forms of labor or machinery, including processing and formulation. There are many different types of manufacturing, including agile, flexible, just-in-time and lean manufacturing. Othe...
The Electronics Industry has grown into a global industry with a value of billions of dollars. Most commonly when referring to the electronics industry it is understood the industry is consumer electronics which produces items used in everyday lif...