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Entry Level Data Annotation Tech Jobs in Phoenix, AZ

HonorHealth

Nuclear Medicine Tech

Scottsdale, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

HonorHealth

CT Tech Lead

Scottsdale, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... marking and annotation as required by CT procedure protocols. Utilizes RIS, PACS and other ...

HonorHealth

Nuclear Medicine Tech

Phoenix, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

HonorHealth

Nuclear Medicine Tech

Scottsdale, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

HonorHealth

Nuclear Medicine Tech

Scottsdale, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

Honorhealth

Nuclear Medicine Tech

Phoenix, AZ

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

HonorHealth

Nuclear Medicine Tech

Phoenix, AZ · On-site

Performs data entry operations using appropriate hospital software package. Staff member may be ... annotation as required by Nuclear Medicine procedure protocols. Utilizes RIS, PACS and other ...

Honorhealth

Radiologic Tech

Phoenix, AZ

Performs data entry operations using appropriate hospital software package. Staff member may be ... and annotation as required by Radiology procedure protocols. Utilizes RIS, PACS and other ...

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Entry Level Data Annotation Tech information

See Phoenix, AZ salary details

$11

$19

$26

How much do entry level data annotation tech jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for entry level data annotation tech in Phoenix, AZ is $19.20, according to ZipRecruiter salary data. Most workers in this role earn between $16.25 and $21.25 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Data Annotation Tech vs Entry Level Data Labeler?

AspectEntry Level Data Annotation TechEntry Level Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech-focusedRemote or on-site, tech-focused
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, autonomous vehicles

Both roles involve labeling data for AI training, requiring similar skills and environments. The main difference lies in terminology; 'Data Annotation Tech' emphasizes the technical aspect of annotation, while 'Data Labeler' is a more general term. Both are entry-level positions vital for AI development in tech industries.

What are some common challenges faced by Entry Level Data Annotation Techs, and how can they be managed?

Entry Level Data Annotation Techs often encounter challenges like maintaining focus during repetitive tasks, ensuring accuracy under tight deadlines, and adapting to evolving annotation guidelines. To manage these, it's helpful to take regular breaks, double-check your work, and actively seek feedback from supervisors. Collaborating with teammates and participating in training sessions can also improve both speed and consistency, making the work more manageable and rewarding.

What is an Entry Level Data Annotation Tech?

An Entry Level Data Annotation Tech is responsible for labeling and categorizing data, such as images, text, or audio, to help train machine learning models. This role typically involves using specialized software to accurately tag and classify data according to specific guidelines. It is a foundational position within the field of artificial intelligence and data science, requiring attention to detail and consistency. No advanced technical skills are usually required, making it a suitable entry point for those interested in AI or data-related careers.

What are the key skills and qualifications needed to thrive as an Entry Level Data Annotation Tech, and why are they important?

To thrive as an Entry Level Data Annotation Tech, you need strong attention to detail, basic computer literacy, and a high school diploma or equivalent. Familiarity with annotation software, data labeling platforms, and basic spreadsheet tools is typically required. Patience, consistency, and effective communication help ensure accuracy and efficient teamwork. These skills and qualities are essential for delivering high-quality labeled data that supports machine learning and AI development.
What are the most commonly searched types of Data Annotation Tech jobs in Phoenix, AZ? The most popular types of Data Annotation Tech jobs in Phoenix, AZ are:
What are popular job titles related to Entry Level Data Annotation Tech jobs in Phoenix, AZ? For Entry Level Data Annotation Tech jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Annotation Tech jobs in Phoenix, AZ look for? The top searched job categories for Entry Level Data Annotation Tech jobs in Phoenix, AZ are:
Entry Level Data Annotation Tech jobs near you

Vision-Language-Action (VLA) Annotator

Objectways Technologies Llc

Phoenix, AZ • Remote

$25/hr

Full-time

Re-posted 7 days ago

Job description

Location:RemoteEmployment Type: Full-Time | 40 hours/week Compensation: $25/hour
About the Role:
We are looking for a detail-oriented and technically capable Vision-Language-Action (VLA) Annotator to join our data operations team in Phoenix, Arizona. In this role, you will be responsible for reviewing, labeling, and quality-checking multimodal datasets used to train and evaluate autonomous driving and robotics models. Your work directly impacts the safety and performance of AI systems operating in the real world.
This is a full-time, 40-hour-per-week position requiring sustained focus, sound judgment, and the ability to apply structured annotation guidelines to complex, real-world scenarios including frequent edge cases.
Key Responsibilities:
  • Review and annotate video footage, sensor telemetry, and camera feeds from autonomous vehicle test drives and robotics platforms.
  • Assess vehicle and robotic behavior in 3D space using 2D camera inputs, including approach angles, following distances, trail alignment, and controlled stop quality.
  • Use time-series telemetry data including speed, throttle, steering, and braking charts to make precise trim and segmentation decisions on data clips.
  • Apply annotation guidelines consistently while exercising independent judgment on ambiguous or edge-case scenarios.
  • Identify and flag unsafe, incomplete, or anomalous driving behaviors (e.g., rolling stops, improper following distance, out-of-distribution maneuvers).
  • Maintain high throughput and accuracy standards; participate in regular quality audits and calibration sessions.
  • Work within annotation platforms (e.g., Encord, CVAT, Label Studio, or similar) to complete labeling tasks efficiently.
  • Document and communicate recurring issues or ambiguities in the data to improve pipeline quality.
Preferred Qualifications:
  • Education: Bachelor's degree with a STEM background preferred (Engineering, Computer Science, Physics, Mathematics, GIS, or related field).
  • Spatial & Mechanical Reasoning: Demonstrated ability to interpret vehicle or robotic behavior in 3D space from 2D camera feeds. Backgrounds in robotics, automotive engineering, mechanical engineering, GIS, or simulation are strong indicators.
  • Time-Series Data Literacy: Experience reading and interpreting sensor data, telemetry charts, lab instrumentation output, or signal processing data. Comfort with chart-heavy analytical workflows is essential for making precise trim decisions.
  • Driving Familiarity: Regular driving experience, ideally in varied or off-road conditions. Must be able to distinguish safe from unsafe driving behavior, recognize complete vs. rolling stops, and assess reasonable following distances.
  • Detail Orientation with Tolerance for Ambiguity: Ability to follow precise, rule-based guidelines while also applying sound judgment on frequent edge cases. Prior experience in QA, data annotation, or lab/research settings is a strong signal.
  • Video Review Endurance: Comfort with sustained video review tasks. Prior experience in video editing, surveillance monitoring, sports performance analysis, or media production is a plus.
Nice-To-Haves:
  • Prior annotation or data labeling experience, especially in autonomy or robotics datasets.
  • Familiarity with geospatial tools, map interfaces, or GIS platforms.
  • Hands-on experience with Encord, Label Studio, CVAT, Scale AI, or comparable labeling platforms.
  • Background in autonomous vehicles, ADAS systems, or driver safety analysis.

This is a remote position.