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Annotation Math Jobs in Provo, UT (NOW HIRING)

Sr Software Engineer, AI Engineer

Lehi, UT

$115K - $151K/yr

Bachelor's, Master's, PhD in Data Science, Mathematics, Computer Science, Computer Engineering ... Data structures, curation, annotation, and pipelines o Model training, fine-tuning, and evaluation

Sr Software Engineer, AI Engineer

Lehi, UT

$115K - $151K/yr

Bachelor's, Master's, PhD in Data Science, Mathematics, Computer Science, Computer Engineering ... Data structures, curation, annotation, and pipelines o Model training, fine-tuning, and evaluation

New

TACHS Tutor

Provo, UT · Remote

$18 - $40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

TACHS Tutor

Spanish Fork, UT · Remote

$18 - $40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

ISEE- Lower Level Tutor

Provo, UT · Remote

$18 - $40/hr

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

Annotation Math information

See Provo, UT salary details

$21.3K

$55.7K

$89.4K

How much do annotation math jobs pay per year?

As of Sep 4, 2026, the average yearly pay for annotation math in Provo, UT is $55,658.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,600.00 and $66,200.00 per year, depending on experience, location, and employer.

What is an annotation math job?

Annotation Math jobs involve labeling, tagging, and categorizing mathematical data, such as equations, formulas, graphs, or written math problems, to create high-quality datasets. These annotated datasets are often used to train artificial intelligence (AI) and machine learning models to recognize and process mathematical content accurately. Annotation Math professionals need a strong understanding of mathematics, attention to detail, and familiarity with annotation tools or platforms. This work is critical for improving technologies like automated math solvers, educational apps, and document digitization.

What are some common challenges faced by professionals in annotation math roles, and how can they be addressed?

Professionals in Annotation Math roles often encounter challenges such as interpreting ambiguous mathematical data, maintaining consistency in labeling complex equations, and managing repetitive tasks that require high attention to detail. Addressing these challenges involves following clear annotation guidelines, collaborating with team members to resolve uncertainties, and utilizing quality assurance tools to minimize errors. Regular feedback sessions and ongoing training also help ensure accuracy and support professional growth in this specialized field.

What are the key skills and qualifications needed to thrive as an annotation math specialist, and why are they important?

To thrive as an Annotation Math Specialist, you need a solid understanding of mathematics, attention to detail, and familiarity with educational or assessment standards, often supported by a relevant degree. Proficiency with annotation tools, data labeling platforms, and sometimes LaTeX or similar mathematical typesetting systems is typically required. Strong analytical thinking, communication, and the ability to work independently are essential soft skills for accuracy and consistency. These skills and qualities are crucial to ensure high-quality, precise annotations that support machine learning, educational resources, or assessment development.

What is the difference between Annotation Math vs Data Annotator?

AspectAnnotation MathData Annotator
Required CredentialsBasic education, sometimes specialized training in annotation toolsHigh school diploma or equivalent, on-the-job training
Work EnvironmentData labeling teams, tech companies, remote or onsiteData labeling teams, tech companies, remote or onsite
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Common Search IntentUnderstanding roles related to data annotation and mathComparing data annotation jobs

Annotation Math and Data Annotator roles both involve data labeling within AI and machine learning industries. Annotation Math may focus more on mathematical annotations, while Data Annotator generally covers broader data labeling tasks. Both roles often share similar work environments and required skills, making them closely related in the data annotation field.

What job categories do people searching Annotation Math jobs in Provo, UT look for?

The top searched job categories for Annotation Math jobs in Provo, UT are:

What cities near Provo, UT are hiring for Annotation Math jobs?

Cities near Provo, UT with the most Annotation Math job openings:

Data Curation/Data Engineer (AI Quality & Evaluation)

US Tech Solutions

Lehi, UT • On-site

$107K - $129K/yr

Full-time

Re-posted 17 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.

US Tech Solutions logo

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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