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Machine Learning Data Annotation Jobs (NOW HIRING)

Bot Auto

Data Annotation Specialist

Houston, TX

Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

Encord

Human Data Operations Strategist

San Francisco, CA · On-site

$150K - $230K/yr

Oversee data annotation projects, translating complex AI and machine learning requirements into clear workflows and instructions for data annotation teams * Ensure the highest standards of data ...

Q ANALYSTS LLC

Data Annotation Technician

Kirkland, WA · On-site +1

... AI) and machine learning (ML). Q Analysts is headquartered in San Jose, CA with a presence ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

Bot Auto

Data Annotation Specialist

Houston, TX · On-site

Collaborate closely with Machine Learning and Mapping engineers to provide feedback on labeling ... Prior experience in data annotation for autonomous driving, robotics, or computer vision.

Apple

Machine Learning Data Engineer

Cupertino, CA · On-site

$141.30K - $169.60K/yr

We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ambiguous data ...

Mercor

Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Coordinate data collection and annotation efforts. * Work with real-time data and content coming from various data sources. * Manage machine learning data pipelines. * Design tests for machine ...

Apple

Machine Learning Data Engineer

Cupertino, CA

$181.10K - $318.40K/yr

Description We are seeking a highly experienced and strategic Machine Learning Data Engineer to drive our machine learning data with a strong focus on quality. In this role, you will transform ...

Mercor

Senior Machine Learning Engineer

New York, NY · Remote

$70 - $100/hr

... experience in Machine Learning , Data Science , Software Engineering , Computer Science ... Prior experience with data annotation, labeling, evaluation, or human feedback collection.

Trimble, Inc.

Machine Learning Data Scientist

Westminster, CO · On-site +1

$122.64K - $165.47K/yr

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

Trimble

Machine Learning Data Scientist

Lake Oswego, OR · On-site

$122.64K - $165.47K/yr

Essential Skills & Experience * 5+ years of expertise in data science or engineering, specifically building and deploying predictive machine learning models. * Proficiency in Python and SQL for data ...

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Machine Learning Data Annotation information

What are the key skills and qualifications needed to thrive as a Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Machine Learning Data Annotation Specialist, you need strong attention to detail, familiarity with data labeling processes, and a basic understanding of machine learning concepts, often supported by a relevant degree or specialized training. Experience with annotation platforms such as Labelbox, Supervisely, or CVAT, and knowledge of data management systems are commonly required. Diligence, consistency, and effective communication are essential soft skills for ensuring high-quality annotated datasets and collaborating with machine learning teams. These skills are crucial for producing accurate training data, which directly impacts the performance and reliability of AI models.

What are some common challenges faced in a Machine Learning Data Annotation role, and how can they be addressed?

One common challenge in a Machine Learning Data Annotation role is maintaining high consistency and accuracy, especially when dealing with large volumes of complex data. Ambiguities in labeling guidelines or unclear data points can also make the work more difficult. To address these issues, annotators often participate in regular training sessions, utilize detailed instruction manuals, and collaborate closely with quality assurance teams. Open communication with project managers and peers is also essential to clarify uncertainties and ensure alignment with project standards.

What is machine learning data annotation?

Machine learning data annotation is the process of labeling or tagging data—such as images, text, audio, or video—so that it can be used to train machine learning models. Annotators add relevant information to raw data, helping algorithms learn to recognize patterns and make predictions. This process is essential for supervised learning, as models require accurately labeled datasets to achieve high performance. Data annotation can be done manually or with the help of specialized tools, and is a critical step in developing reliable AI systems.

What is the difference between Machine Learning Data Annotation vs Data Labeler?

AspectMachine Learning Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing centers, AI companies
Industry UsageAI, machine learning, data scienceData management, AI, machine learning
Job FocusCreating labeled datasets for training AI modelsLabeling data to assist AI training

Machine Learning Data Annotation involves creating detailed labels and annotations for datasets used to train AI models, often requiring understanding of specific data types. Data Labelers focus on applying labels to data, typically with less emphasis on complex annotations. Both roles are essential in AI development, but data annotation often involves more specialized tasks and tools.

More about Machine Learning Data Annotation jobs
What are the most commonly searched types of Machine Learning Data Annotation jobs? The most popular types of Machine Learning Data Annotation jobs are:
What job categories do people searching Machine Learning Data Annotation jobs look for? The top searched job categories for Machine Learning Data Annotation jobs are:
Machine Learning Data Annotation jobs near you
Infographic showing various Machine Learning Data Annotation job openings in the United States as of May 2026, with employment types broken down into 67% Full Time, and 33% Part Time. Highlights an 67% In-person, and 33% Remote job distribution.
Machine Learning Data Linguist, Alexa AI

Machine Learning Data Linguist, Alexa AI

Amazon

Seattle, WA

$130.30K - $156.50K/yr

Full-time

Posted 16 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,788 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers

Job description

Amazon is seeking a Machine Learning Data Linguist to join our Alexa AI team. This role focuses on language data, primarily in the areas of text annotation and general data analysis deliverables.
The ML Data Linguist must have a passion for data, efficiency, accuracy, and should be capable of:
- Handling unique data analysis requests from a range of data customers
- Providing data quality expertise to other team members and coaching improvements
- Delivering high quality work in a fast-paced environment
- Working autonomously with minimum direction
- Building a thorough understanding of conventions and providing support to global sites
- Understanding changes to conventions deployed in response to customers' requests and modifying workflows accordingly
- Contributing to process improvements to reduce handling time and improve output
- Improving software tools by identifying bugs and suggesting enhancements
- Diving deep into issues and implementing solutions independently
- Proactively addressing issues and problems
- Keeping up with changing project conventions and priorities
Key job responsibilities
- Label, generate, and ensure the quality of datasets.
- Work closely with ML Data Linguists and scientists to understand data ambiguities and resolve issues in annotation guidelines.
- Conduct in-depth qualitative error trend analysis, developing action plans to enhance data quality.
- Collaborate with ML Data Linguists, scientists, and Ops Managers to drive innovation in processes, tracking, and annotation workflows.
A day in the life
Most days are spent collecting requirements from customers, collaborating with peers and stakeholders to complete deliverables, and recommending process improvements.
About the team
The work that we do is confidential, but we are a highly collaborative team who obsess over our internal and external customers.

What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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