Supervised Artificial Intelligence (AI) and Machine Learning (ML) learning need training data sets that educate models to identify certain sorts of input and create outputs. The number of data labeling jobs is increasing as the number of AI and ML projects expands. This has become a potential chance for businesses. In this article, let’s find out with Wow AI about the ultimate guide to finding labeling jobs.
What is data labeling?
Data labeling is the process in machine learning of recognizing raw data (pictures, text files, videos, etc.) and adding one or more relevant labels to provide context. Based on that, a machine learning model may learn from it.
Labels, for example, might identify whether a photograph has a bird or an automobile, which words were said in an audio recording, or whether an x-ray shows a tumor.
Data labeling is necessary for many applications, including computer vision, natural language processing, and speech recognition.
How does data labeling work?
Massive volumes of data are frequently required by ML and deep learning systems to lay the groundwork for consistent learning patterns. The data they utilize to guide learning must be labeled or annotated in accordance with data characteristics that assist the model in organizing the input into patterns that yield the intended result.
Data collection
Begin by gathering a large amount of data: photographs, movies, audio files, texts, and so forth. When opposed to a limited amount of data, a huge and diversified amount of data ensures more reliable outcomes.
Data tagging
Human labelers detect items in unlabeled data using a data labeling platform in data tagging. They may be asked to assess whether or not an image contains a person, or to follow a ball in a movie.
Quality Assurance
To construct high-performing ML models, your labeled data must be useful and accurate. If you don't have a quality assurance (QA) mechanism in place to assess the accuracy of your labeled data, your ML model will fail to function properly.
What does a data labeler do?
Although data labeler is a fairly simple task, it is known by several distinct titles. A data annotator, a data (or label) associate, a data expert, a machine learning labeler, and so on are all examples of job titles. This should not be confused with that of a data scientist or an AI engineer because such roles demand a deeper grasp of developing and implementing an ML algorithm.
Data labelers are in high demand
According to
McKinsey, considerable workplace and job demand changes will be in place by 2030. Automation will result in the abolition of 5% of all occupations. Simultaneously, one-third of the 60 percent of occupations will be mechanized, paving the way for the transitions.
Nonetheless, AI and ML not only "destroy" jobs, but also generate new ones. Experts believe that in this AI future, data scientists, AI engineers, and data labelers will thrive.
Job description of data labeler
Data labelers assist computer models in locating and recognizing certain pictures. Data labelers work using a platform that allows them to construct bounding boxes around certain photos and label them in a way that the model understands. Data labeling work can vary depending on what the AI or ML model is designed to do:
Data labeling for picture recognition requires the ability to pay attention to detail. For example, the data labeler must construct the bounding box around just the region of the image where the model has the qualities given in the label, whether "tree," "bicycle," or "cat".
Data Labeler’s Job Description
A data labeler needs the following skills (but not limited to):
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Attention to details: Annotating a bit more or less of the item, omitting certain parts of it, or inaccurate tagging will have little effect on the overall procedure. However, if you make enough of these little errors, the model's training may be endangered.
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Focus on long periods of time: Perseverance is necessary traits when doing data labeling. A data labeler should be able to sit down and focus on what's on the screen without being easily distracted and making mistakes as a result.
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Focus on Tech: Data annotation requires working with computers rather than people. It may be hard for some people while a great career choice for others. As a trade-off, a data labeler can work online and part-time, which is a perfect option for a freelancer who doesn't possess enough skills or wants to change the type of job they've been doing.
Salary for data labeler
The salary for data labelers is different in projects and companies as well as the backgrounds of the applicants. But it seems like the median hourly wage is somewhere around $3- $10 an hour.
Where to find jobs in data labeling?
There are a number of ways to find legit data labeling jobs, especially if you are looking for freelance jobs.
Apply for data labeling jobs in crowdsourcing companies
For those who are new to the fields, the best way is to find companies specializing in Artificial Intelligence and Machine Learning which are actively offering crowdsourcing jobs like
Wow AI. Those companies would have various projects that require data labelers as freelancers.
The requirements to join these projects are pretty simple as anyone who has wifi connection, smartphones, or laptops with good English skills can do it. For each project, the specific requirements for data labeling freelancers would be different but the process is also simple. You will then fill in the recruitment form and receive the test to do it.
If you pass the test, the company will send you the contract, rule and payment methods accordingly. You will work with the team to receive tasks and deadlines with specific instructions. Once you submit and your tasks are approved, you will then receive the payments based on previous agreements. The period of receiving the payments will depend on different projects and companies.
Apply for data labeler position at the in-house team
In-house data labeling secures the highest quality labeling possible and is generally done by data scientists and data engineers hired at the organization.
High-quality labeling is crucial for industries like insurance or healthcare, and it often requires consultations with experts in corresponding fields for the proper labeling of data. These jobs are often open to those who have experience in the field.
To find data-labeling jobs as experienced professionals, you can search on some job sites such as Indeed, Waw Asia, or LinkedIn.
Interested In Taking Up Data Labeling Jobs? Check Out Wow AI’s New Projects
By now, we hope you got an idea of a guide to finding data labeling jobs. As we said, anyone can join freelance jobs in data labeling.
Wow AI wants to make the process of finding data labeling jobs as freelancers simple for you. We handpicked different types of crowdsourcing projects with questions that anyone can do.
