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Annotation Labelling Jobs in Dallas, TX (NOW HIRING)

... annotation policies that require an understanding of both technical and operational constraints • Have a solid understanding of project guidelines to be able to communicate labeling concepts ...

Delivery Lead

Dallas, TX · Remote

$110K - $140K/yr

... annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the ...

High Volume (TOFU) Recruiter

Dallas, TX · On-site +1

$55K - $100K/yr

... annotation to delivery. We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the ...

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

... labeling/annotation; - Strong analytical skills, exceptional attention to detail, and sharp pattern recognition abilities; - Proven experience reviewing, processing, and navigating high-volume ...

Annotation Labelling information

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Dallas, TX? For Annotation Labelling jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Dallas, TX look for? The top searched job categories for Annotation Labelling jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Annotation Labelling jobs? Cities near Dallas, TX with the most Annotation Labelling job openings:
Data Labeler Manager

Data Labeler Manager

Tesla

Dallas, TX • On-site

Full-time

Posted 28 days ago


Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 676 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers


Job description

Job Summary:
Tesla is a leading company in the electric vehicle and AI space, seeking a Data Labeler Manager to oversee a team responsible for annotating data for their AI software. The role involves managing performance, ensuring data integrity, and collaborating with engineering teams to enhance the efficiency of data labeling operations.
Responsibilities:
• Conduct ongoing performance management: create coaching plans, track progress, conduct monthly 1:1’s, and complete monthly analyst reports
• Evaluate daily performance in proprietary software to report daily summaries and team metrics to ensure the team is consistently exceeding expectations
• Work directly with engineers and Tesla AI leadership and own annotation policies that require an understanding of both technical and operational constraints
• Have a solid understanding of project guidelines to be able to communicate labeling concepts effectively, labeling inefficiencies, assist in creating documentation and training materials
• Execute proper headcount allocation between quality control, labeling, and prioritize job queues daily as directed by leadership
• Ensure documentation and daily planning for the team is accurate and consistently updated
• Ensure team alignment with company policies
• Other supervisory duties such as employee development, conducting bi-yearly performance reviews and monthly performance check-ins with Team Leads and Data Labelers, and accurately manage timekeeping
Qualifications:
Required:
• Experience managing and motivating medium-sized teams that perform manual operations
• Ability to manage time efficiently, prioritizing tasks by order of precedence and completing in a timely manner
• Proven record of accomplishments executing and meeting sensitive deadlines with experience managing multiple competing projects with limited resources
• Strong problem-solving skills, with an aptitude for quickly learning systems with minimal training and can adapt in an ambiguous environment
• Effective communication and presentation skills - can explain complicated topics and ideas in a clear and concise manner
• Commitment to data accuracy and throughput
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

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