7 Entry-Level Machine Learning Jobs To Kickstart a Career

Machine learning is among the most exciting fields in the software industry today. In fact, Indeed dubbed the role of machine learning engineer as the best job available on the US job market. Job openings for machine learning engineers grew by 340% between 2015 and 2018, showing that there’s plenty of demand to match the influx of talent in this space.

If you aspire to a job in machine learning, you’ve got plenty of options in front of you. So many options, in fact, that it can be hard to figure out which job is the right one for you.

If that’s where you’re at, then we’ve got you covered. Below, we’ll take a look at the most popular entry-level machine learning roles and cover the job skills associated with each of them. That way you have a better understanding of what you’re signing up for and can chart out your path toward the machine learning career that’s best suited for you.

Is It Easy To Land an Entry-Level Machine Learning Job?

Not if you have the right skill and education. Because of the breadth of skills required to work in this space, the barrier to entry can be high. So to land a job, you need to focus on enhancing your technical prowess while also working on projects that you can put on your portfolio. 

7 Entry-Level Machine Learning Jobs

Let’s now take a look at some of the most common entry-level machine learning engineer job types out there. We’ll find out what machine learning skills each of these roles require, job responsibilities, and the annual salary on offer. 

Machine Learning Intern

Machine learning intern is something of a broad job title that will give you hands-on experience with a wide range of skills in this field. Depending on the requirements of your company, you may be tasked with developing new machine learning algorithms, analyzing datasets, or building and testing machine learning models. 

That might seem like a lot of different job responsibilities rolled into one but that’s what a machine learning internship is all about. It’s an opportunity to find out how all these different advanced technologies are deployed in the real world and determine which machine learning position you want to pursue as a career. 

How Much Can You Make

The average salary for machine learning interns in the United States is $88,581.

Educational Qualifications, Skills, and Other Basic Requirements 

Companies usually pick machine learning interns from applicants who are currently enrolled in a relevant college degree. That usually means a bachelor’s degree in computer science or mathematics. You might also be considered if you’ve just completed a machine learning bootcamp and want to gain some real-world skills. 

You don’t need to possess advanced skills in any one area of machine learning to work as an intern. Rather, what’s required is a general skill set that you can apply to different business challenges. And most importantly, you should be able to learn new things on the job and pick up the rigors of a professional environment quickly. 

Junior Machine Learning Engineer

The junior machine learning engineer role is a position in which you’ll get a taste of developing self-contained machine learning systems. You’ll work with data scientists, software engineers, and database architects to develop both supervised and unsupervised learning systems and create models with predictive capabilities. 

Machine learning engineer roles also involve a lot of work with data. You’ll often be tasked with finding or putting together datasets on which your models can be trained. You might also use data visualization techniques to comprehend your own findings and present them to different stakeholders in your organization. 

How Much Can You Make

The average base salary for junior machine learning engineers is $124,813.

Educational Qualifications, Skills, and Other Basic Requirements

Junior machine learning engineers usually land their job after earning a degree in computer science or mathematics. Companies also consider candidates who have completed machine learning bootcamps. 

You need to have a strong foundational understanding of a few areas of mathematics to work as a machine learning engineer. That includes basic calculus, linear algebra, and statistics. 

Given that this is an engineering role, you’ll also need to know how to work with programming languages—Python, C++, and Java are among the most commonly used. If you’re new to programming, then it’s recommended that you start with Python and work your way to other languages if your job demands it. 

Junior Data Scientist

Data scientist is one of those job roles that’s really gained prominence in the tech industry over the past few years. That’s partly because of the demand for data professionals and the increased importance of data across industries. 

As a junior data scientist, you will be asked to contribute to just about any task that involves data in your organization. That means that you’ll need to get good at building datasets, cleaning data, and building custom analytics applications. 

How Much Can You Make

Junior data scientists make $88,237 annually on average.

Educational Qualifications, Skills, and Other Basic Requirements

You will generally be asked to have at least a bachelor’s degree in computer science or information technology to apply to junior data scientist roles. But it is increasingly becoming possible to land these jobs if you’re self-taught and have a strong portfolio of data science projects.

Big data is all the rage these days and you will have to get good at working with it. Working with large data volumes is a skill in itself and you will be tested in that ability in your work as a junior data scientist. Building predictive models, designing recommendation systems, and creating segmentation algorithms are some of the skills that will come in handy in that regard. 

Software engineering skills are increasingly becoming a requirement for data scientists. You will boost your prospects by gaining an understanding of the software development lifecycle and having a working knowledge of a framework like agile software development. 

Junior Data Engineer

Data engineers are professionals who concern themselves with engineering data handling systems. Their job begins with analyzing the requirements of a project and coming up with a suitable data architecture. They then set about implementing that architecture and fleshing out its different parts. 

Junior data engineers are usually assigned to work on specific parts of that process. The big-picture stuff is usually left to senior data engineers. Junior professionals work on conducting research, implementing data collection systems, and analyzing data manipulation techniques. 

How Much Can You Make

Junior data engineers have an average annual salary of $105,426.

Educational Qualifications, Skills, and Other Basic Requirements

A bachelor’s degree in computer science or a related field is usually a requirement for data engineering jobs. You can further boost your profile with a graduate degree in data science or mathematics. 

SQL is a key skill for anyone who wants to work as a data engineer. It’s a technology that you will use often to work on relational database systems. So you’ll need to get good at writing queries in SQL and using it to manipulate the data in your databases. 

Another key skill in this field of machine learning is data architecture. Data engineers need to have a strong understanding of data-dependent processes and develop systems that have project-specific characteristics. Apache Hadoop is a machine learning tool that you can use to streamline your work in that area. 

Junior AI Engineer

AI engineering is an exciting job role in which you’ll be asked to develop the code and architecture for artificially intelligent systems. These are computational systems that mimic human intelligence in the way that they’re able to comprehend data and learn from it. 

The specific area of AI that you work on will depend on the goals of your project. Natural language processing, image processing, and deep learning are some of the areas that you can find yourself working in. 

How Much Can You Make

The average annual salary of a junior AI engineer in the USA is $79,173.

Educational Qualifications, Skills, and Other Basic Requirements

AI engineers come from educational backgrounds in computer science, mathematics, and physics. You will need to have at least a bachelor’s degree to be considered for most jobs in this area. 

AI engineers have a strong understanding of data structures and algorithms. Developing algorithms is a core part of this job role. You’ll use techniques like logistic regression, random forests, and linear regression to create algorithms and build AI models. 

Automation is another important skill to pick up as an AI engineer. You’ll need to get good at automating processes that deal with data collection and processing. Various frameworks are used to carry out this work, including TensorFlow, Theano, and PyTorch. 

Junior Data Analyst

Data analysis is the process of uncovering patterns that are hidden deep within large datasets. The job of junior data analysts involves finding relevant datasets and analyzing them to produce valuable business insights. 

Data analysis is a multi-step process that includes data collection, cleaning, analysis, and reporting. Junior data analysts are assigned to one or more of these steps in each project. You’ll find yourself working in a larger team and with other stakeholders such as project managers and data engineers. 

How Much Can You Make

Junior data analysts have an average salary of $62,088.

Educational Qualifications, Skills, and Other Basic Requirements

Increasingly, data analysts are being hired from bootcamps and courses. There are also various online degrees that you can take with a focus on data analysis. If you do want to take a more conventional route, then a degree in computer science is the way to go. 

The most basic skill you will need as a data analyst is, of course, data analysis. There are various techniques that are used to analyze data that you need to have a working understanding of. 

Junior Business Intelligence Developer

Business intelligence (BI) is a field that’s emerged as a focus for organizations making data-driven decisions. Business intelligence developers pick specific business problems and work on ways to solve them using data. 

Business intelligence developers focus on the data that are produced at an organizational level. They collate this data and use it as the raw material for the analysis process. A strong BI process can help organizations find new business opportunities, optimize costs, and improve employee productivity. 

How Much Can You Make

The average salary of business intelligence developers is $101,851.

Educational Qualifications, Skills, and Other Basic Requirements

Business intelligence is a field where you need to have both technical chops and a thorough understanding of business processes. On the technology front, it’s imperative to have a strong understanding of data analysis, databases, and software engineering. SQL, Python, and Tableau are some of the technologies that you’ll use as part of your work. 

There are various tools that are commonly used by professionals in the business intelligence sector. They provide assistance with tasks such as data mining, statistics analysis, and big data analytics. If you aspire to a job in this field, you should be proficient with tools such as Microsoft Power BI, Zoho Analytics, or SAP Business Intelligence.

Tips To Land Your First Machine Learning Job

Here are a few things that you can do to maximize your chances of landing a job in the machine learning industry.

Polish and Tailor Your Resume

When applying to machine learning roles, you have to do two important things. The first is to tailor your resume for the job that you’re applying to. You’ll definitely want to check out our guide to crafting a machine learning resume.

Have a Strong Portfolio

A portfolio is a proof that you can get the job done. Recruiters love to see a portfolio with a few items that are highly relevant to the vacancy. The best way to get started is by contributing to open source projects and then working your way up to your personal machine learning projects. 

Your Network Is Your Net Worth

It’s essential that you build your network gradually as you work on your machine learning skills. Usually, it’s a lot easier to land a job through a referral as compared to the standard interview process. You can grow your network by connecting with machine learning professionals on LinkedIn and attending events for software professionals locally. 

Know the Latest Trends

Machine learning is a field that’s at the cutting edge of the software industry. There’s always something new popping up that could change how you work as a machine learning professional. We’ve put together a list of resources that you can use to keep up with the latest goings-on in the industry. 

Pursue an Internship

Going from an undergraduate course or machine learning bootcamp straight into a job can sometimes be a bit of a big leap. A good stop in between is a machine learning internship. That’s an opportunity to gain some real-world experience without the pressures of a full-time role. Read more about how you can land an AI internship here. 

Getting Into Machine Learning: Real-Life Stories and Examples

Devansh – Machine Learning Made Simple

A lot of us want to breeze through our machine learning journey in a few months. But here’s someone who took five years to go from beginner to expert, which is a much more realistic timeframe. Devansh’s story shows us that picking up skills in this area is a long-term commitment and can be a rewarding process if you stick with it. 

Patrick – AssemblyAI

Patrick is a machine learning developer advocate at AssemblyAI. In this video, he discusses how he would go about studying machine learning if he could start all over again. It’s a great watch because you get to watch a machine learning professional reflect on their journey and can learn how to do it better if you’re just starting out. The AssemblyAI YouTube channel is a great resource for technical machine learning content as well as career advice.

FAQs About Landing an Entry-Level Machine Learning Job

We’ve got the answers to your most frequently asked questions:

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