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 ...
Data Annotation Engineer information
See Orem, UT salary details
$44.8K - $56.3K
2% of jobs
$56.3K - $67.8K
9% of jobs
$75.8K is the 25th percentile. Wages below this are outliers.
$67.8K - $79.3K
20% of jobs
$79.3K - $90.8K
4% of jobs
$90.8K - $102.3K
4% of jobs
$102.3K - $113.8K
1% of jobs
$113.8K - $125.3K
0% of jobs
$125.3K - $136.8K
0% of jobs
The median wage is $142.5K / yr.
$136.8K - $148.3K
18% of jobs
$148.3K - $159.8K
0% of jobs
$164.2K is the 75th percentile. Wages above this are outliers.
$159.8K - $171.3K
41% of jobs
$44.8K
$128.2K
$171.3K
How much do data annotation engineer jobs pay per year?
As of Jul 29, 2026, the average yearly pay for data annotation engineer in Orem, UT is $128,198.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,000.00 and $170,400.00 per year, depending on experience, location, and employer.
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.
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.
Does data annotation really pay?
Data annotation engineers can earn competitive wages, often paid hourly or per task, with pay rates varying based on experience, complexity of annotations, and the platform or employer. Entry-level roles may start at minimum wage, while experienced annotators or those with specialized skills can earn higher salaries or freelance rates. Overall, data annotation can provide a reliable income, especially for remote or flexible work arrangements.
What is the highest salary for data annotator?
The highest salary for a data annotation engineer can reach up to $80,000 to $100,000 annually, depending on experience, location, and the complexity of annotation tasks. Senior roles or those with specialized skills in tools like Labelbox or CVAT may earn higher compensation. Salaries vary widely across companies and regions but generally reflect the technical skills required for high-quality data labeling.
What is a data annotation engineer?
A data annotation engineer is a professional responsible for labeling and annotating data, such as images, text, or videos, to prepare it for machine learning models. They often use specialized tools and follow guidelines to ensure data quality, supporting the development of AI systems.
How hard is it to get hired by data annotation?
Getting hired as a data annotation engineer typically requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require advanced degrees, but strong accuracy and consistency are important for success in the role.
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 popular job titles related to Data Annotation Engineer jobs in Orem, UT? For Data Annotation Engineer jobs in Orem, UT, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Orem, UT look for? The top searched job categories for Data Annotation Engineer jobs in Orem, UT are:
What cities near Orem, UT are hiring for Data Annotation Engineer jobs? Cities near Orem, UT with the most Data Annotation Engineer job openings:
Tesla rating
8.5
Based on 679 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.