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Freelance Machine Learning Engineer

In the Information Technology sector, Machine Learning Engineer is considered the most sought-after career. It is not a purely academic field. It requires knowledge from both the data science field and software engineering.

What is Machine learning?

Machine Learning is a subfield of artificial intelligence and computer science. It is concerned with the use of data and the creation of algorithms that mimic the process of human learning. Machine learning is concerned with the creation of systems capable of autonomously accessing and using data. Machine learning’s primary goal is to execute computer programs autonomously.

What is Freelance Machine Learning Engineer?

Machine learning engineer is different from data scientist and data analyst. Data analysts are supposed to analyze the data. A human is doing the task. While, as far as machine learning engineer is concerned, the end product is working software, and that software interacts with other software components with the minimal human role.

Lately, the demand for data scientists and machine learning engineers is on the rise. Therefore, machine learning engineers shifted to a global market of freelancing. Independent freelancing not only provides opportunities but also helps freelancers in achieving their career goals.

Skills Important for Freelance Machine Learning Engineer:

Skills that are considered essential for freelance machine learning engineers include knowledge of Computer Science fundamentals, programming, data structures, algorithms, computer architecture, and computability. Machine learning engineers should also know how to manage probability, statistics, data modeling, and evaluation. Last but not least is the applicability of machine learning algorithms and libraries as machine learning works as working software.

Steps to be taken to become Freelance Machine Learning Engineer:

Following are the essentials steps that should be taken to become a potential freelance machine learning engineer:

Create a personalize web page

Profile creation and set up a portfolio is a crucial step when you enter into a freelancing market. The profile must include your contact, skills, academic credentials, work experience, and muses as well. You may find online web pages available.

Build a portfolio on freelancing websites

Websites which have colossal market value are Upwork and Fiverr. There are lots of other platforms which provide services. These websites help freelance machine learning engineers in connecting with companies that hire them. Toptal is one of the renowned freelancing platforms which companies use to look out for freelance machine learning engineers.

Take part in community events

The next step is to participate in community events to increase your exposure and showcase your talents. It also helps you in gaining valuable information related to work, challenges, and opportunities. There are many online and physical community events such as Meetup, Gitter, Kaggle, and MLConf Job Board.

Demonstrate your skills

Whether you are a novice or an expert, your portfolio should document all of your abilities and accomplishments. Maintain a public repository for your whole codebase. GitHub and BitBucket are both excellent platforms for this kind of service. Maintain a clean repository so that others can access and download your codes for their projects.

What do Machine Learning Engineers Make

Machine learning engineers create self-learning artificial intelligence systems that simplify the usage of predictive search models, interactive help, translation tools, chatbots, and autonomous cars: They create computers that comprehend, use algorithms to ensure that their predictions are accurate, and solve issues using data sets.

Employers need talented designers who can assist them in improving their machine learning applications. Engineers collaborate with their organizations to develop artificial intelligence technologies that benefit real-world users. Consider a useful self-learning program that learns from data. An engineer’s job is to test and analyze existing machine-learning (ML) processes in order to address data set issues and increase the capacity of AI applications to predict the future based on their data. To ensure they continue progressing ahead, an ML engineer may demonstrate extensive knowledge of data science and experience working in a comparable ML position. A skilled machine learning engineer will understand how to improve the performance of predictive automation software. Engineers that specialize in machine learning and deep learning create applications and study techniques. Additionally, a machine learning developer will collaborate with managers to establish goals, develop AIs and machine software for self-running automation of prediction models, convert data science experiments, select appropriate machine learning algorithms and tools, and ensure that the correct algorithms are used. By assigning names to pictures and deciphering how text-to-speech conversions operate, artificial intelligence (AI) engineers transform unstructured and disorganized data into useable information. They handle complex issues using a diverse set of data and improve the accessibility of existing machine learning libraries and algorithms. Engineers may use machine learning algorithms to analyze large amounts of historical data in order to forecast and comprehend research findings from testing and statistical analysis.

The news of machine learning excites people all across the globe. As a machine learning engineer, your work has become a bit simpler in recent years as a result of the development of open-source and private software, tools, and libraries. Additionally, the number of software tools for engineers has increased as firms use AI and machine learning, implying that they are now accessible to a broader audience. Several critical tools are shown below.

  • Azure Machine Learning
  • RapidMiner
  • Pytorch
  • TensorFlow
  • WEKA
  • Scikit-Learn

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