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Data Annotation Manager Jobs in Utah (NOW HIRING)

Tesla

Data Labeler Manager

Draper, UT · On-site

... and own annotation policies that require an understanding of both technical and operational ... Data Labelers, and accurately manage timekeeping Qualifications : Required : • Experience ...

Kimley-Horn

Right of Way/Survey Civil Designer

Lehi, UT · On-site

... annotation, file setup, and sheet generation * Ability to read and interpret survey data, ROW ... Strong organizational and time management skills; able to meet deadlines without close supervision

Kimley-Horn

Right of Way/Survey Civil Designer

Lehi, UT · On-site

... annotation, file setup, and sheet generation * Ability to read and interpret survey data, ROW ... Strong organizational and time management skills; able to meet deadlines without close supervision

Cacheflow

Software Engineer (Full Stack)

Lehi, UT · On-site

$100 - $140/hr

... for managing the hourly workforce. There are 2.7 billion hourly workers, making up 80% of the ... Our Robotics team develops scalable data collection and annotation pipelines that enable the ...

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Utah

Data Annotation Manager information

See Utah salary details

$28.2K

$88.4K

$156.6K

How much do data annotation manager jobs pay per year?

As of Aug 26, 2026, the average yearly pay for data annotation manager in Utah is $88,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,100.00 and $114,300.00 per year, depending on experience, location, and employer.

What does a data annotation manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

What are the key skills and qualifications needed to thrive as a data annotation manager?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What are some common challenges faced by data annotation managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

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

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Utah?

The most popular types of Data Annotation jobs in Utah are:

What are popular job titles related to Data Annotation Manager jobs in Utah?

For Data Annotation Manager jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Data Annotation Manager jobs in Utah look for?

The top searched job categories for Data Annotation Manager jobs in Utah are:

What cities in Utah are hiring for Data Annotation Manager jobs?

Cities in Utah with the most Data Annotation Manager job openings:

Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Utah as of August 2026, with employment types broken down into 84% Full Time, 9% Part Time, and 7% Contract. Highlights an 77% In-person, 6% Hybrid, and 17% Remote job distribution, with an average salary of $88,438 per year, or $42.5 per hour.

Data Curation/Data Engineer (AI Quality & Evaluation)

US Tech Solutions

Lehi, UT • On-site

$107K - $129K/yr

Full-time

Re-posted 8 days ago

Job description

Job Summary:
US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. They are seeking a Data Curation/Data Engineer to join their AI team and ensure the highest standards of quality, safety, and performance across AI-driven product offerings. The role involves collaborating with cross-functional teams to develop and maintain high-quality datasets and AI systems.
Responsibilities:
• Architect and implement frameworks to enforce AI quality, safety, and evaluation standards.
• Design and maintain scalable data pipelines for data ingestion, curation, annotation, and validation.
• Develop comprehensive evaluation methodologies and datasets to measure model accuracy, safety, and performance.
• Test, refine, and optimize ML models for both edge devices and cloud environments.
• Partner closely with embedded, app, platform, QA, product, and UX teams to deploy AI solutions at scale.
• Monitor production AI systems, analyze performance metrics, and drive continuous improvement.
• Establish best practices for data governance, reproducibility, and model lifecycle management.
Qualifications:
Required:
• 3–5 years of relevant experience in AI/ML, data engineering, model evaluation, or AI quality engineering.
• Strong analytical and problem-solving skills.
• Data structures, data curation, annotation workflows, and dataset lifecycle management.
• Model training, fine-tuning, and evaluation.
• LLM and Generative AI training/evaluation.
• Computer vision training, validation, and deployment.
• Transformers, LLMs, Vision-Language Models (VLM), and knowledge graphs.
• Classification, object detection, segmentation, tracking, recognition, Re-ID, pose estimation, and vector embeddings.
• Model compression techniques.
• Image, audio, radar, and signal processing.
• Advanced proficiency in Python.
• Shell scripting.
• C++ and/or Rust.
• Embedded Linux environments.
• Git version control.
• Experience working with secure, scalable, high-availability, low-latency, and distributed systems.
• Bachelor’s, Master’s, or PhD in Data Science, Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or related field.
Company:
US Tech Solutions counted among the largest yet the fastest growing staffing firm; all achieved organically. Founded in 2000, the company is headquartered in Toronto, CAN, with a team of 1001-5000 employees. The company is currently Late Stage.
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About US Tech Solutions

Sourced by ZipRecruiter

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Jersey City, NJ, US

Year founded

2000

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