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Assistant Ai Labeling Jobs in Arizona (NOW HIRING)

Waabi

Senior Software Engineer, Auto Labelling

Phoenix, AZ · On-site +1

$170K - $220K/yr

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Waabi

Senior Software Engineer, Auto Labelling

Phoenix, AZ · On-site +1

$170K - $220K/yr

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Align Communications

Cabling Associate

Phoenix, AZ · On-site

$20.50 - $25.75/hr

This position requires 75% travel to project sites nationwide, including AI build locations. Key ... labeling, routing, and test results while reinforcing jobsite safety. * Assist with cabling ...

The Archetype Strategy

Lead Technician

Phoenix, AZ · On-site

$40K - $51K/yr

... terminations, labeling, testing, and clean-up * Ensure all work is performed according to site ... Maintain a clean, organized, and safe work environment * Assist with conflict resolution and ...

Deloitte

Cyber Data Protection Manager

Gilbert, AZ · Remote

$110K - $149K/yr

DLP, sensitivity labels, data classification, DSPM, DSPM for AI, on-demand classification, or ... Perform the role of mentor and coach to assist junior staff to develop skills by providing feedback ...

TSMC

AMHS Department Assistant

Phoenix, AZ · On-site

... AI and digital future. TSMC Core Values At TSMC, we invite talented individuals who share our ... Color vision requirements for label/tool/report status interpretation Shift Structure TSMC is 24/7 ...

Align Communications

Cabling Associate

Phoenix, AZ · On-site

$20.50 - $25.75/hr

This position requires 75% travel to project sites nationwide, including AI build locations. Key ... labeling, routing, and test results while reinforcing jobsite safety. * Assist with cabling ...

TSMC

AMHS Department Assistant

Phoenix, AZ

... AI and digital future. TSMC Core Values At TSMC, we invite talented individuals who share our ... Color vision requirements for label/tool/report status interpretation Shift Structure TSMC is 24/7 ...

TSMC

AMHS Department Assistant

Phoenix, AZ · On-site

... AI and digital future. TSMC Core Values At TSMC, we invite talented individuals who share our ... Color vision requirements for label/tool/report status interpretation Shift Structure TSMC is 24/7 ...

Dick's Sporting Goods

Teammate Footwear

Mesa, AZ

$16.75 - $22.50/hr

As a Teammate - Footwear , you will assist with product selection, merchandise expertise, and ... AI tools are not permitted to be used by the candidate during any part of the interview process.

Dick's Sporting Goods

Teammate Footwear

Glendale, AZ · On-site

$17 - $22.50/hr

As a Teammate - Footwear , you will assist with product selection, merchandise expertise, and ... AI tools are not permitted to be used by the candidateduring any part of the interview process.

Dick's Sporting Goods

Teammate Footwear

Glendale, AZ · On-site

$17 - $22.50/hr

As a Teammate - Footwear , you will assist with product selection, merchandise expertise, and ... AI tools are not permitted to be used by the candidate during any part of the interview process.

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130K - $177K/yr

As a Senior Data Engineer in the AI Data Curation track, you will ensure that the data powering our ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

TSMC

Senior Data Engineer / Data Curator

Phoenix, AZ

$130K - $177K/yr

As a Senior Data Engineer in the AI Data Curation track, you will ensure that the data powering our ... Experience with data annotation tools and platforms for manual or semi-automated labeling.

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All JobsAi Labeling JobsAssistant Ai Labeling JobsAssistant Ai Labeling Jobs in Arizona

Assistant Ai Labeling information

What's the easiest AI job to get?

Entry-level AI-related jobs like data labeling or annotation are generally the easiest to obtain, as they require minimal technical skills and often offer flexible schedules. These roles involve reviewing and tagging data to help train AI models and typically do not require advanced degrees or certifications.

What is the difference between Assistant Ai Labeling vs Data Annotator?

AspectAssistant Ai LabelingData Annotator
CredentialsHigh school diploma or equivalent; some roles may require basic technical skillsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentRemote or office-based; collaborative with AI teamsPrimarily remote; focused on data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics
Search & Comparison IntentUnderstanding roles supporting AI trainingData labeling and annotation tasks for AI models

Assistant Ai Labeling involves supporting AI systems by labeling data, often requiring some technical understanding. Data Annotator focuses on labeling data to prepare datasets for AI training. Both roles are essential in AI development, with overlapping skills but different focus areas.

What is an AI labeling job?

An AI labeling job involves reviewing and annotating data such as images, videos, or text to help train machine learning models. Workers typically use specialized tools to add tags or labels that enable AI systems to recognize patterns and make decisions. These jobs often require attention to detail and may be performed remotely with flexible schedules.

How to become a data labeler?

To become a data labeler, you typically need basic computer skills, attention to detail, and the ability to follow instructions. Many positions require no formal education, but familiarity with data annotation tools and understanding of the specific data type (images, text, audio) can be helpful. Some companies may require completing a training or assessment before starting the job.

What are Assistant AI Labeling jobs?

Assistant AI Labeling jobs involve reviewing, tagging, and categorizing data such as images, text, or audio to help train artificial intelligence and machine learning models. These roles are essential because accurate labeling ensures that AI systems can learn to recognize patterns and make decisions effectively. Tasks may include drawing bounding boxes around objects in images, transcribing spoken words, or classifying text according to given guidelines. The work is often done using specialized software and requires attention to detail as well as consistency. Assistant AI Labelers may work remotely or in-house for tech companies, research organizations, or data annotation firms.

What are some common challenges faced by Assistant AI Labeling professionals, and how can they be addressed?

Assistant AI Labeling professionals often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially with ambiguous or subjective cases. To address these challenges, most teams implement clear annotation guidelines, regular training sessions, and peer review processes to ensure high-quality outputs. Collaboration with data scientists and project managers is also key, as open communication helps clarify uncertainties and align labeling practices with project goals. Embracing feedback and staying flexible as guidelines evolve can further enhance both the quality of work and job satisfaction in this role.

What are the key skills and qualifications needed to thrive as an Assistant AI Labeling Specialist, and why are they important?

To thrive as an Assistant AI Labeling Specialist, you need strong attention to detail, accuracy, and an understanding of data annotation practices, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools, and sometimes basic knowledge of programming languages like Python is beneficial. Dependability, time management, and the ability to follow complex instructions are crucial soft skills for excelling in this role. These skills ensure high-quality labeled data, which is vital for training accurate and reliable AI models.

How much do data labelers typically earn?

Data labelers, including assistant AI labelers, typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the employer. Some positions may offer project-based pay or bonuses for accuracy and efficiency.
What are the most commonly searched types of Ai Labeling jobs in Arizona? The most popular types of Ai Labeling jobs in Arizona are:
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Assistant Ai Labeling jobs near you

Senior Software Engineer, Auto Labelling

Waabi

Phoenix, AZ • On-site, Remote

$170K - $220K/yr

Full-time

Posted 16 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.
 
With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will...
- Be part of a team of multidisciplinary Research Scientists and Engineers working on building a cutting-edge offline perception and auto-labelling system leveraging computer vision, and machine learning.
- Manage the end-to-end orchestration of the large-scale auto-labelling training, evaluation and automation eco-system.
- Architect and scale the pipeline to handle large-scale data and user requests using distributed computing frameworks.
- Collaborate with ML researchers and engineers to seamlessly deploy new architectures into the production environment.
Qualifications:
- Bachelors degree with a Computer Science, Robotics and/or similar technical field(s) of study.
- 3+ years of experience developing solutions in ML systems or the ML software stack.
- Deep understanding of ML system architecture, performance analysis, and profiling tools to optimize complex workloads.
- Experience with the end-to-end productionization of deep learning models, particularly large-scale online inference.
- Proficient in Python with a track record of writing high-quality, well-structured, and well-tested "production-grade" code.
- Open-minded and collaborative team player with the willingness to help others.
 
Bonus/nice to have:
- Familiarity with 3D data (LIDAR/Point Clouds) and multi-modal sensor fusion perception models.
- Experience working with large Vision-Language Models (VLMs)
The US yearly salary range for this role is: $170,000 - $220,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations. Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 
 
Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!
 
Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.