Data Labeler Manager
Draper, UT · On-site
... 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 ...
Data Labeler Manager
Draper, UT · On-site
... 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 ...
... hands-on data work, including annotation and transcription tasks • Demonstrate exceptional ... engineering teams • Familiarity with researching resources such as data repositories and code ...
... hands-on data work, including annotation and transcription tasks • Demonstrate exceptional ... engineering teams • Familiarity with researching resources such as data repositories and code ...
Data Annotation Engineer information
See Utah salary details
$46.9K - $58.9K
2% of jobs
$58.9K - $71K
9% of jobs
$79.4K is the 25th percentile. Wages below this are outliers.
$71K - $83K
20% of jobs
$83K - $95.1K
4% of jobs
$95.1K - $107.1K
4% of jobs
$107.1K - $119.1K
1% of jobs
$119.1K - $131.2K
0% of jobs
$131.2K - $143.2K
0% of jobs
The median wage is $149.2K / yr.
$143.2K - $155.3K
18% of jobs
$155.3K - $167.3K
0% of jobs
$172K is the 75th percentile. Wages above this are outliers.
$167.3K - $179.3K
41% of jobs
$46.9K
$134.2K
$179.3K
How much do data annotation engineer jobs pay per year?
As of May 30, 2026, the average yearly pay for data annotation engineer in Utah is $134,244.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,500.00 and $178,400.00 per year, depending on experience, location, and employer.
What is a Data Annotation Engineer job?
A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.
What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?
To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.
What are the main challenges faced by Data Annotation Engineers in their daily work?
One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.
More about Data Annotation Engineer jobs
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What job categories do people searching Data Annotation Engineer jobs in Utah look for? The top searched job categories for Data Annotation Engineer jobs in Utah are:
What cities in Utah are hiring for Data Annotation Engineer jobs? Cities in Utah with the most Data Annotation Engineer job openings:
Full-time
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Tesla rating
8.5
Based on 661 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.
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.