Land Your Dream Machine Learning Job in 2025

We’re in the new year and if you’ve been scoping the job market, you probably think finding a job is nearly impossible. It does feel like this. Many organisations are downsizing, they don’t have money, and more and more jobs are becoming automated. It’s a scary time to be trying to find a job.

In this article, I will go through 5 pointers on how to help you secure your dream job. Stop making the same mistakes over and over again and learn about the different ways you can land your ideal machine learning position.

1. Show Off Your Skills

 
Let’s be honest: there’s so much you can provide in your resume without it becoming a small biography. Therefore, you need to find other ways to showcase your skills. By doing this, you will show your future employer the skills you have and the value you can bring to the organisation. GitHub and other platforms allow you to show off your skills through project-based work, providing your future employer insights into your skillset.

Another way you can showcase your skills and go above and beyond is through open source code. There is a ridiculous amount of open source code out there and some is not top-notch. If you find a bug in Hugging Face’s open source code, you can run your tests, ensure your fixes have improved, and create a pull request. You can communicate with the team at Hugging Face, showcase your skills, and hopefully land a job with them (it has happened before).

2. Work On Projects

 
There are a lot of projects out there and what you need to be doing is figuring out how to find them and continue to actively look for them. Working on projects is what is going to set you apart from the competition. A lot of people focus on doing course after course and rarely realise the importance of applying your learned skills to real-life projects.

Not every project is going to be great but one or two with great value can make a big difference to you landing a job.

3. Look For Companies

 
If you want to go a step further and do projects for specific companies to really showcase your skills. To do this, you will need to expand your current network as well as consistently be informed on what is new. One of the best ways to do this is by subscribing to newsletters such as The AI Report which sends out weekly newsletters informing you of what is new in the market. With this information, you can check out new research papers or company releases that may be interested in project-based work.

Another tip is checking out startups. It is easy for people to levitate towards the big companies but don’t lose sight of the value of startups and what they can offer in the long game. There are a lot of organisations that have recently raised funding and will be looking for project-based work; you can check some of them out here.

4. Network Like Hell!

 
Networking is generally not taught to AI and machine learning professionals. However, knowing the right people is so important to your career growth. If you do not know anybody to help you get in the door, you will never be able to improve your career.

Don’t shut yourself out from networking events. Many machine learning professionals have work for home jobs, and as a result they rarely get out to connect with people. Networking events are a great opportunity for you to attend professional conferences or tech meetups which will allow you to connect with tons of people from different scopes.

One way networking can help you with your next job is by cold emails, which may not be ideal, but sometimes works. You could land your first machine learning job and then this connection can help you with your next role, the next one, and so on. You can also use platforms such as LinkedIn to network with people who have more years of experience and understanding of the sector which can guide you as well as help you with mentoring, jobs, etc.

5. Make People Find You

 
Why not make people find you, rather than you going out to find them?

This goes back to showcasing your skill. When you do a new project, or learn something new, why not share it online and see where your social media posts or blog posts land? They may fall into the hands of your next employer; you just never know.

You can use platforms such as Medium to showcase your projects as a blog, LinkedIn to create social media posts, or create a YouTube channel and create videos. There are various ways you can create content and it can make a difference in helping your next employer find you rather than you searching for them.

Wrapping Up

 
These 5 tips are to help you try different ways to land your dream machine learning job rather than sitting around waiting for the vacancy you applied for to reply. Sometimes you have to make the moves to create your next move.
 
 

Nisha Arya is a data scientist, freelance technical writer, and an editor and community manager for KDnuggets. She is particularly interested in providing data science career advice or tutorials and theory-based knowledge around data science. Nisha covers a wide range of topics and wishes to explore the different ways artificial intelligence can benefit the longevity of human life. A keen learner, Nisha seeks to broaden her tech knowledge and writing skills, while helping guide others.