Machine Learning Data Labeler Job Description [Updated for 2025]

In the era of artificial intelligence, the focus on Machine Learning Data Labelers has never been more pronounced.
As technology continues to evolve, the demand for proficient individuals who can accurately label, manage, and refine our machine learning datasets grows ever stronger.
But let’s delve deeper: What is truly expected from a Machine Learning Data Labeler?
Whether you are:
- A job seeker trying to understand the depth of this role,
- A hiring manager outlining the ideal candidate,
- Or simply fascinated by the intricate world of machine learning,
You’re in the right place.
Today, we present a customizable Machine Learning Data Labeler job description template, designed for effortless posting on job boards or career sites.
Let’s get started.
Machine Learning Data Labeler Duties and Responsibilities
Machine Learning Data Labelers play a crucial role in the development of artificial intelligence and machine learning algorithms.
They are responsible for accurately labelling and categorizing data which is then used to train and improve machine learning models.
Their daily duties and responsibilities include:
- Analyzing and interpreting complex data sets
- Labeling data accurately to ensure it fits the correct categories for machine learning
- Working closely with data scientists and engineers to understand the requirements of the machine learning models
- Using data labeling tools to tag data with relevant labels
- Ensuring data integrity by performing quality checks and identifying any errors or inconsistencies in the data
- Creating clear and comprehensive reports on the labeling process and any challenges encountered
- Keeping up to date with the latest developments in machine learning and data labeling techniques
- Maintaining confidentiality and following data privacy rules while handling sensitive data
Machine Learning Data Labeler Job Description Template
Job Brief
We are seeking a diligent and detail-oriented Machine Learning Data Labeler to join our team.
This role involves assigning labels to data, such as images or text, which will then be used to train machine learning models.
The ideal candidate will have an understanding of data annotation tools, excellent attention to detail, and the ability to meet tight deadlines.
The candidate will also have a basic understanding of machine learning concepts and algorithms.
Responsibilities
- Reviewing, processing, and labeling data accurately and within specified timelines.
- Collaborating with machine learning engineers to understand labeling needs and requirements.
- Validating and ensuring the quality of annotated and labeled data.
- Improving data labeling efficiency through the use of data annotation tools.
- Providing feedback to engineers and managers on any issues, inconsistencies, or improvements needed in the data labeling process.
- Maintaining confidentiality and adhering to data privacy regulations.
Qualifications
- High school diploma or equivalent.
- Experience in data entry, data labeling, or similar role.
- Knowledge of data annotation tools is desirable.
- Understanding of basic machine learning concepts and algorithms.
- Strong attention to detail and accuracy.
- Ability to work independently and as part of a team.
- Excellent communication skills.
Benefits
- 401(k)
- Health insurance
- Dental insurance
- Retirement plan
- Paid time off
- Professional development opportunities
Additional Information
- Job Title: Machine Learning Data Labeler
- Work Environment: Office setting with options for remote work. There may be periods of high-volume data labelling projects.
- Reporting Structure: Reports to the Data Labeling Supervisor or Machine Learning Engineer.
- Salary: Salary is based upon candidate experience and qualifications, as well as market and business considerations.
- Pay Range: $45,000 minimum to $80,000 maximum
- Location: [City, State] (specify the location or indicate if remote)
- Employment Type: Full-time
- Equal Opportunity Statement: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- Application Instructions: Please submit your resume and a cover letter outlining your qualifications and experience to [email address or application portal].
What Does a Machine Learning Data Labeler Do?
Machine Learning Data Labelers work primarily in the technology and AI industries.
Their primary role is to annotate and label data that is used to train machine learning models.
They work closely with Data Scientists and Machine Learning Engineers, providing them with the labeled data needed for the development of AI algorithms.
They are responsible for the quality and accuracy of the data used in these models.
Their tasks include reviewing data sets, including images, text, and more, and adding relevant tags or labels to them.
These labels help the machine learning models to understand and learn from the data.
In addition, they also verify the accuracy of existing labels and make corrections as necessary.
They play a crucial role in validating the data used in machine learning, ensuring that the algorithms will perform as expected.
Data Labelers need to have an understanding of the specific use case of the machine learning model they are working on, as this will influence how they label the data.
They also need to keep up with the latest developments in the field of machine learning and AI.
Besides, they may also be involved in data preprocessing tasks such as data cleaning and data transformation, ensuring that the data is in the right format for the machine learning models.
Machine Learning Data Labeler Qualifications and Skills
Machine Learning Data Labelers play a critical role in the development of machine learning models, and they should have qualifications and skills such as:
- Understanding of machine learning concepts and the significance of data labeling in the training of machine learning models.
- Attention to detail to ensure accurate labeling and categorization of data.
- Proficiency in the use of data labeling tools and software to create annotated data for machine learning algorithms.
- Strong analytical skills to interpret complex data sets and apply appropriate labels.
- Good communication skills to work effectively with data scientists and machine learning engineers in aligning data labeling with the needs of machine learning models.
- Problem-solving skills to identify issues with data sets and fix or report them accordingly.
- Persistence and patience to handle repetitive tasks involved in data labeling without compromising on quality.
- Understanding of the domain-specific knowledge to comprehend the nuances of the data for effective labeling.
Machine Learning Data Labeler Experience Requirements
Entry-level candidates for the role of Machine Learning Data Labeler may have 1 to 2 years of experience in the field of data science or a related area.
This experience can be gained through internships, part-time roles or academic research projects involving data cleaning, classification and annotation.
Aspiring Machine Learning Data Labelers should also have experience with software tools used for data labeling such as Labelbox, Prodigy, or Supervisely.
Additionally, they are expected to have knowledge of machine learning concepts and algorithms which can be obtained through coursework or self-study.
Candidates with more than 3 years of experience may have worked in roles such as Data Analyst, Data Scientist, or Machine Learning Engineer, where they gained experience in curating datasets for machine learning models.
They may also have experience in creating data labeling guidelines and quality assurance protocols.
Those with more than 5 years of experience in the field are often proficient in scripting languages such as Python or R, and have a deep understanding of machine learning algorithms.
They may have worked on complex projects involving large-scale data labeling and have experience leading a team of data labelers or managing outsourcing relationships with data labeling service providers.
In some cases, companies may seek Machine Learning Data Labelers with domain-specific expertise, such as medical imaging or autonomous vehicles, as these roles may require specialized knowledge to correctly label and interpret data.
Machine Learning Data Labeler Education and Training Requirements
Machine Learning Data Labelers typically possess a bachelor’s degree in fields like computer science, data science, statistics, or related fields.
Having foundational knowledge in mathematics and statistics is essential, as they will need to interpret and analyze complex datasets.
Familiarity with machine learning algorithms and the ability to work with large and complex data sets are also crucial skills for this role.
Experience with programming languages such as Python, R, or SQL is often required.
Understanding of data structures and database systems, along with proficiency in tools like Excel, is necessary for this role.
Many employers also expect Machine Learning Data Labelers to have prior experience in data labeling, data classification, and data cleaning.
While not always necessary, a master’s degree in data science or a related field can provide advanced expertise and may be preferred by some employers.
In addition, certain certifications related to data science and machine learning, such as the Certified Analytics Professional (CAP) or Microsoft Certified: Azure AI Engineer Associate, can demonstrate a candidate’s commitment to the field and their proficiency in specific skills.
Continued education and staying updated with the latest developments in machine learning, data labeling techniques, and tools is highly recommended for career growth in this field.
Machine Learning Data Labeler Salary Expectations
A Machine Learning Data Labeler earns an average salary of $58,000 (USD) per year.
The actual earnings may vary based on the labeler’s experience, level of education, geographical location, and the complexity of tasks in the project.
Machine Learning Data Labeler Job Description FAQs
What skills does a Machine Learning Data Labeler need?
Machine Learning Data Labelers need good analytical skills to categorize and label data accurately.
They should have strong attention to detail to spot any inconsistencies in data, and be familiar with the machine learning process to understand how their work fits in the bigger picture.
A basic understanding of data structures, programming languages, and machine learning algorithms is beneficial.
Do Machine Learning Data Labelers need a degree?
The requirements for becoming a Machine Learning Data Labeler can vary.
However, most positions often require at least a bachelor’s degree in Computer Science, Statistics, or a related field.
Some positions may require knowledge of specific areas like natural language processing, image recognition, or data processing tools.
What should you look for in a Machine Learning Data Labeler resume?
You should look for proven experience in data analysis, data labeling, or data management.
Familiarity with machine learning models and concepts, as well as proficiency in tools used for data labeling, can be a big plus.
If the role is more specialized, relevant experience in the specific domain (like medical, autonomous driving, etc.) is important.
What qualities make a good Machine Learning Data Labeler?
A good Machine Learning Data Labeler is meticulous and has a strong attention to detail as data labeling requires precise classification of data.
They should be patient and methodical, as the process can be repetitive and time-consuming.
Good problem-solving skills and the ability to work independently are also crucial for this role.
What are the daily duties of a Machine Learning Data Labeler?
On a typical day, a Machine Learning Data Labeler might start by reviewing their assigned datasets and the guidelines for labeling.
They then spend much of their day classifying data accurately according to these guidelines.
They may also participate in team meetings to discuss progress, challenges, and strategies for efficiency.
They also need to routinely check their work for quality and consistency.
Is it difficult to hire Machine Learning Data Labelers?
Hiring Machine Learning Data Labelers can be a challenge due to the specific skill set required for the role.
It can be difficult to find candidates who possess the right mix of technical skills and attention to detail.
Moreover, because this role is relatively new and evolving rapidly, finding experienced candidates can be tough.
Conclusion
And there we have it.
Today, we’ve unraveled the intricacies of what it truly means to be a Machine Learning Data Labeler.
Surprised?
It’s not just about labeling data.
It’s about shaping the future of artificial intelligence, one data set at a time.
With our comprehensive Machine Learning Data Labeler job description template and real-world examples, you’re ready to stride ahead.
But why limit yourself?
Delve further with our job description generator. It’s your ultimate tool for creating laser-precise listings or honing your resume to immaculate precision.
Remember:
Every piece of labeled data is a stepping stone towards a smarter AI.
Let’s create that future. Together.
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