Image by Editor | Midjourney and Canva
It’s a new year, and if you’ve been scouring the job market, you’re probably thinking that finding a job is nearly impossible. It certainly feels like this. Many organizations are downsizing, running out of money, and more and more jobs are being automated. It’s a scary time to look for a job.
In this article, we will discuss 5 points to help you secure your dream job. Stop making the same mistakes over and over again and learn about different ways to land your ideal machine learning position.
1. Show off your skills
Honestly, there’s a lot you can put on your resume without it becoming a mini-biography. Therefore, you need to find another way to show off your skills. By doing so, you can demonstrate to potential employers the skills you have and the value you can bring to the organization. GitHub and other platforms allow you to showcase your skills through project-based work, giving potential employers insight into your skillset.
Another way to showcase your skills and go above and beyond is by using open source code. There’s a crazy amount of open source code out there, and some of it isn’t top-notch. If you find a bug in Hugging Face’s open source code, you can run tests, see improvements to the fix, and create a pull request. You can communicate with the Hugging Face team, show off your skills, and hopefully find work with them (this has happened to me before).
2. Work on a project
There are a lot of projects out there and all you have to do is figure out how to find them and keep actively looking for them. Working on projects will help you differentiate yourself from your competitors. Many people focus on completing course after course and rarely realize the importance of applying the skills they learn to real-world projects.
Not every project will be great, but one or two projects of great value can make a big difference in getting the job.
3. Search for companies
If you want to go a step further and work on a project for a specific company and really put your skills to work. To do this, you need not only to expand your current network, but also to constantly obtain new information. One of the best ways to do this is to subscribe to newsletters such as The AI Report, which sends out weekly newsletters that keep you informed of what’s new in the market. You can use this information to check for new research papers and company releases that may be of interest to you for project-based work.
Another tip is to check out startups. It’s easy for people to get carried away towards big companies, but we must never lose sight of the value of startups and what they can offer in the long run. There are many organizations that have recently raised funding and are looking for project-based work. You can see some here.
4. Hellish network!
Networking is not typically taught to AI and machine learning experts. However, knowing the right people is critical to your career growth. If you don’t have someone to help you get in, you won’t be able to advance your career.
Don’t be locked out of networking events. Many machine learning professionals work from home, so they rarely get out and connect with people. Networking events are a great opportunity to attend professional conferences and technical meetups, and connect with many people from different fields.
One method of networking that will help you land your next job is cold email. This may not be ideal, but it may work. Once you land your first machine learning job, this connection can help you in your next role, and then the next, and so on. You can also use platforms like LinkedIn to network with people who have years of experience and understanding of the field and can provide guidance, work, and other support.
5. Let people find you
Why not let people find you instead of you going looking for them?
This goes back to showing off your skills. When you do a new project or learn something new, why not share it online and see where your social media posts and blog posts get posted? They may end up in the hands of your next employer. you never know.
You can use platforms like Medium to showcase your project as a blog, LinkedIn to create social media posts, or create a YouTube channel to create videos. There are many ways to create content that will help your next employer find you instead of you searching.
summary
These five tips will help you explore different ways to land your dream machine learning job instead of just waiting to hear back from the jobs you applied for. Sometimes you have to take action in order to create your next move.
Nisha Arya I’m a data scientist, freelance technical writer, editor and community manager at KDnuggets. She is particularly interested in providing data science career advice, tutorials, and theory-based knowledge about data science. Nisha covers a wide range of topics and is interested in exploring the different ways in which artificial intelligence can benefit human longevity. An avid learner, Nisha aims to expand her technology knowledge and writing skills while helping to mentor others.
