IN THIS ARTICLE
- Why Consider a Freelance Machine Learning Engineer Career?
- How to Get Started as a Freelance Machine Learning Engineer?
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In the past few years, the demand for data scientists and machine learning engineers are on the rise. There are lots of career opportunities for machine learning engineers and it’s becoming one of the most sought after positions in the IT industry. As a freelance machine learning engineer, there are plenty of opportunities for you to work with leading organisations and help them make the right decisions and increase their chances of success. Sounds interesting? Continue reading to see how you can get started with this career as a freelance machine learning engineer.
Why Consider a Freelance Machine Learning Engineer Career?
With the demand and the market for freelancers, solopreneurs and consultants on the rise, most organisations are on the move from hiring full-time resources to working with freelancers. The advantage of working with freelancers is that they are more affordable than full-time resources, flexibility in working hours, and get things delivered swiftly and quickly. Statistics also show that 20% of large organisations use 30%+ remote workers. Well-known companies like Trello, Basecamp etc, make 100% use of freelancers and work with remote teams.
How to Get Started as a Freelance Machine Learning Engineer?
Build a personalised web page or profile
Build a portfolio on freelancing websites
Take part in Community Events
Demonstrate your skills
With the advancements of artificial intelligence, machine learning engineers are becoming necessary for everyday business operations. This article will help you get started as a freelance ML engineer by taking advantage of the best freelancing platforms available out there.
1. Build a personalised web page or profile
The first way to make a career as a freelance machine learning engineer is to create a personalised website/portfolio profile. This should list all the work that you have done so that organisations use your profile to see if you are fit for the project or not. Make sure you provide a contact email address or contact information so that you can be contacted easily. LinkedIn Profile – Yes! You can also build your profile on LinkedIn as organisations look into LinkedIn when they look for machine learning engineers. You can become a part of LinkedIn groups and have discussions with the group members to improve your machine learning knowledge.
2. Build a portfolio on freelancing websites
Talk about freelancing and the first few names you will hear are Upwork, Freelancer and so on. There are lots of other freelancing websites where you can get your profile listed with your experience levels and skills. Freelancer websites help to connect freelance machine learning engineers with the companies who want to hire them. Let’s take a look at some of the platforms –
Toptal is one of the widely used sites by companies to look out for freelance machine learning engineers. Only the best-of-best stand the chances to get into Toptal (roughly about 3% of the applications). But if your application is accepted into Toptal, be assured to get world-class job openings from organisations around the world. To get started with Toptal, create an account and enter your portfolio details with the skill set information. Once your application has been submitted, you will be required to clear a live screening test and an interview with Toptal. After the interview, you will be given an assignment (a test project) which you must turn around within two or three weeks. Once you clear all these steps and if your application has been accepted, your profile will automatically be matched with projects.
Upwork is one of the well-known freelancing websites. Every person starting their career as a freelancer will have an Upwork profile. It is a good starting place as there are already plenty of registered clients who will require the services of freelance machine learning engineers. Getting started with Upwork is simple. Sign up for an account, submit a cover letter of why you would make a difference if given the opportunity and add your skills, work experience, list of previously worked projects, and other information, as necessary. Your profile will be submitted for review and if accepted, you will start receiving projects.
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3. Take part in Community Events
Once you have created your online profile, the next step is to increase your exposure by taking part in community events. Frequent participation in community events will help you showcase your talents, and at the same time gain valuable information from the attendees. There are plenty of online/physical community events that are available and it’s important that you register and become a part of the most renowned ones, such as –
This is one of the most popular networking platforms. You can register to be a part of live events with fellow machine learning engineers and data scientists.
Gitter is a Slack community where you can join with people working in the data science and machine learning field and have chats with them over a Slack Channel.
Kaggle is a community of machine learning engineers, data scientists. The community often hosts events, competitions and aids the community of developers with learning materials and courses. For people looking out for jobs in the ML space, look out for the Kaggle job board.
MLConf Job Board
MLConf, known as Machine Learning Conference, offers a job posting board for organisations to fill in their job requirement of a machine learning engineer. It’s completely free and MLConf brings together machine learning engineers from around the world into a single place where organisations can find their talent.
4. Demonstrate your skills
Be it if you are a beginner or an experienced geek, make sure you build your machine learning portfolio that will keep track of your complete skillsets. Keep all your code-base in a public source code repository such as GitHub or BitBucket. Make sure you keep your repository as clean as possible with ready to use instructions so that other people can download your code and reuse it for their project work.
There are many ways in which you can become a freelance machine learning engineer. It’s very important that you remain patient and focused during the initial stages. Every step that is outlined above will eventually turn out to become a positive step forward in the right direction. So if you are convinced to get started and kickstart your career as a freelance machine learning engineer, Springboard can help you achieve your dream. Register today for Springboard’s Machine Learning Career Track that offers real-world projects, 1:1 mentorship, career coaching and a job guarantee and become a certified machine learning engineer in just six months.
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