ZipRecruiter

Log In

1

Data Annotation Tech Jobs in Dallas, TX (NOW HIRING)

LJB, Inc.

Survey CAD Tech

Richardson, TX · On-site

$65K - $85K/yr

... annotation guidelines to ensure consistent quality, increased efficiency, and ease of data ... SURVEY CAD TECH ESSENTIAL CREDENTIALS: Required Qualifications: * 3+ years of field survey and data ...

Caterpillar

Product Owner- Data Engineering

Irving, TX · On-site

$128K - $192K/yr

Technology, Digital and Data Your Work Shapes the World at Caterpillar Inc. When you join ... Knowledge of data ingestion, data hauling/connectivity, data ontology, annotation architecture ...

YO AI Labs

Medical Coder - Remote

Dallas, TX · Remote

$50 - $80/hr

Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to accuracy, quality, and continuous learning in healthcare coding and technology

YO AI Labs

Korean Language Expert

Dallas, TX · Remote

$65 - $100/hr

Collaborate with project participants to improve data collection, evaluation, and annotation ... Familiarity with language technology, digital content platforms, or AI-related projects is a plus.

Forhyre

Prompt Engineers

Plano, TX · On-site

We are a cutting-edge technology company at the forefront of the Artificial Intelligence (AI ... Solid knowledge of data collection, preprocessing, and annotation for prompt development.

Semantix

Enterprise Solutions AI Consultant

Dallas, TX · On-site

... AI, Technology, and Data solutions; we are the engine behind the global AI revolution. As we ... annotation, and generative AI services-to Fortune 500 leaders. TransPerfect AI offers a premier ...

previous pagenext page

Showing results 21-40

All JobsData Annotation Tech JobsData Annotation Tech Jobs in Dallas, TX

Data Annotation Tech information

See Dallas, TX salary details

$12

$22

$34

How much do data annotation tech jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for data annotation tech in Dallas, TX is $22.69, according to ZipRecruiter salary data. Most workers in this role earn between $16.73 and $26.97 per hour, depending on experience, location, and employer.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What are the most commonly searched types of Data Annotation Tech jobs in Dallas, TX?

The most popular types of Data Annotation Tech jobs in Dallas, TX are:

What are popular job titles related to Data Annotation Tech jobs in Dallas, TX?

For Data Annotation Tech jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Data Annotation Tech jobs in Dallas, TX look for?

The top searched job categories for Data Annotation Tech jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Annotation Tech jobs?

Cities near Dallas, TX with the most Data Annotation Tech job openings:

Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Dallas, TX as of September 2026, with employment types broken down into 33% Full Time, 33% Part Time, and 34% Contract. Highlights an 100% Remote job distribution, with an average salary of $47,201 per year, or $22.7 per hour.

Senior Data Scientist

Westlake, TX • On-site

Fidelity Investments
Investment Management and Consulting Services • 10K+ employees
Learn more about Fidelity Investmentsexternal

Full-time

Re-posted 29 days ago

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 274 frontline employees who took The Breakroom Quiz

Job description


Senior Data Scientist - Applied AI, NLP, and LLM Solutions
Note: Fidelity will not provide immigration sponsorship for this position
Fidelity Workplace Investing is seeking hands-on, builder-oriented Senior Data Scientists with experience in applied AI, natural language processing, large language models, machine learning, and knowledge graph technologies. This position will be based full time in either Westlake, TX or Merrimack, NH.
The Purpose of Your Role
This individual will lead high-profile applied data science and artificial intelligence initiatives across Workplace Investing, working closely with Technology, Product Management, AI/ML Engineering, and others. The role will focus on developing and evaluating AI-based solutions using natural language processing (NLP), large language models (LLM), machine learning (ML), knowledge graphs, agentic AI patterns, and other advanced or emerging techniques. Key assignments may include document processing and information extraction, schema mapping, enterprise assistants, recommender systems, and anomaly detection.
The successful candidate must be comfortable operating in a fast-paced and sometimes ambiguous environment working with current and emerging AI technologies. They will be expected to gather and analyze data from multiple structured and unstructured data sources, develop reliable models and evaluation frameworks, interpret and clearly communicate findings to technical and business audiences. They will support a broad range of applied AI initiatives with the highest degree of quality, partner effectively with engineering teams to move solutions into production, and thrive in a high-performing, collaborative work environment. The ideal candidate combines strong data science fundamentals with product instincts, technical curiosity, and a track record of delivering measurable business impact.
The Skills You Bring
  • PhD in Computer Science, Information Science, Statistics, or a related STEM discipline with focus on AI, machine learning, natural language processing, deep learning, knowledge graphs, or related methods; OR a Master's Degree in a related field with 3 or more years relevant professional experience
  • Strong technical foundation in machine learning and statistical modeling, with deeper experience in one or more applied AI areas such as natural language processing, large language models, deep learning, knowledge graphs, or related methods.
  • Strong Python and SQL programming skills with demonstrated proficiency in data extraction, data engineering, exploratory analysis, feature engineering, data modeling, pipeline automation, and model evaluation.

  • Solid verbal communication, presentation, and technical writing skills with an ability to explain complex data science, statistics, and computer science concepts clearly to nontechnical audiences.
  • Experience or working knowledge in one or more applied AI areas such as information retrieval, question answering, chatbot evaluation, retrieval-augmented generation, or agentic AI frameworks.
  • Exposure to intelligent document processing use cases, which may include document classification, OCR, key-value extraction, signature or seal detection, annotation strategy and dataset creation, and evaluation of extraction quality.
  • Working knowledge of embedding models, vector representations, semantic similarity clustering, or dimensionality reduction techniques such as t-SNE or UMAP.
  • Experience in one or more predictive modeling areas such as recommendation systems, ranking models, ensemble methods, anomaly detection, statistical process control, time-series monitoring, threshold strategies, or alert-quality evaluation.
  • Experience designing or contributing to AI/ML evaluation and monitoring frameworks, including benchmark datasets, labeled and synthetic test data, model and prompt comparison, precision/recall analysis, error analysis, latency assessment, cost-quality tradeoff analysis, and production monitoring with tools such as Fiddler.

The Value You Deliver
  • Lead the data science and model development components of projects involving large language models, natural language processing, knowledge graphs, and related applied techniques.
  • Design, build, and deploy applied AI solutions across NLP, LLMs, document processing, schema mapping, recommendation, and anomaly detection use cases.
  • Lead data analysis with diverse scope and complex business and technical challenges
  • Develop best practices for data science, considering the full analytical lifecycle
  • Ensure the delivery of high-quality, trustworthy data science by developing guidelines and rigorous evaluation frameworks for AI/ML solutions.
  • Implement new technologies in a production environment with product, IT, and data engineering teams
  • Present reports and findings to senior-level technical and nontechnical audiences

How Your Work Impacts the Organization
As a data scientist in Fidelity Workplace Investing, you will contribute to advancing the analytics and data science capability for a variety of employee benefit products and will take the organization to the next level.
Fidelity's Onsite Working Model
Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles. Currently, some roles and locations require 100% onsite presence, while others require less. Onsite expectations are likely to evolve as the rollout continues. This transition does not apply to fully remote roles.
Certifications:
Category:
Data Analytics and Insights
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

What Fidelity Investments employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply