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Full Time Machine Learning Data Annotation Jobs in Dallas, TX

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... data warehouse platform using the Snowpark framework Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable ... Data Analysis: Analyze large, diverse data sets to identify patterns, trends, and insights that ...

You'll work with large-scale image and video data, building and optimizing production-grade vision ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

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Showing results 1-20

Full Time Machine Learning Data Annotation information

See Dallas, TX salary details

$37.1K

$121.4K

$194.4K

How much do full time machine learning data annotation jobs pay per year?

As of Aug 28, 2026, the average yearly pay for full time machine learning data annotation in Dallas, TX is $121,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $134,500.00 per year, depending on experience, location, and employer.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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

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

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Dallas, TX?

For Full Time Machine Learning Data Annotation jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Dallas, TX look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Full Time Machine Learning Data Annotation jobs?

Cities near Dallas, TX with the most Full Time Machine Learning Data Annotation job openings:

Infographic showing various Full Time Machine Learning Data Annotation job openings in Dallas, TX as of July 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 14% Part Time, 15% Contract, 34% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $121,417 per year, or $58.4 per hour.

Machine Learning & Data Platform Engineer

RealPage, Inc.

Richardson, TX • On-site

$107K - $182K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 18 days ago


RealPage rating

6.0

Company rating: 6.0 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

226th of 246 rated software companies


Job description

We are looking for a Staff Engineer to own and evolve our financial data integration and ML classification platform. This system ingests hundreds of variations of real estate financial reports — trial balances, rent rolls, budgets, forecasts, aged receivables — from property management companies, automatically detects their format, classifies their structure using ML models, and transforms them into normalized data for downstream analytics. 

You will be the primary technical lead across two critical systems: a document parsing engine handling 280+ specialized ETL processors and a dynamic pipeline orchestration platform that uses ML-predicted field mappings to automate data extraction at scale. This role demands breadth — you will build ML models, maintain production data pipelines, design database schemas, and make architectural decisions independently. You will also mentor and manage one direct report.


  • ML Model Development & Deployment — Build, train, and deploy classification models (currently served via Wallaroo) that predict financial field/table mappings from document headers. Extend existing BERT-based question-answering models used for extracting structured data from free-text property descriptions.
  • Pipeline Platform — Maintain and extend the configuration-driven orchestration system that matches incoming files to processing pipelines, executes dynamic conditionals, and writes standardized output to downstream templates.
  • ETL Engine — Evolve the parsing library that handles complex Excel workbooks with nested headers, multi-tab structures, merged cells, and varied accounting system formats (ARES, GIC, DCS).
  • Data Quality & Reliability — Improve prediction accuracy, expand audit logging, and ensure processing integrity across clients and document types.
  • Architecture & Technical Leadership — Drive technical decisions on model serving infrastructure, database schema design, and API integration patterns with RealPage's Data Management Gateway (DMG). Provide mentorship and technical guidance to your direct report. 

  • 5+ years Python development with production ML systems 
  • Strong experience with NLP / text classification — specifically training and fine-tuning transformer models (Hugging Face, TensorFlow) for document understanding tasks
  • Deep proficiency with pandas, NumPy, SQLAlchemy, and PostgreSQL
  • Experience building and maintaining ETL pipelines that process messy, semi-structured data (Excel, CSV) at scale
  • Familiarity with ML model serving platforms (Wallaroo, SageMaker, Vertex AI, or similar) including OAuth2-based inference APIs
  • Comfort operating as a technical lead — triaging bugs, shipping features, making architectural calls independently, and mentoring junior engineers
  • Demonstrated ability to work across the full stack of a data platform: from raw file ingestion through model inference to API integration 

Preferred 

  • Domain experience in real estate finance, property management, or accounting data (chart of accounts, trial balances, rent rolls) 
  • Experience with SFTP-based file processing workflows and Paramiko 
  • Familiarity with dynamic code generation / evaluation patterns for configurable data transformations 
  • Background in document parsing / OCR / intelligent document processing 
  • Experience with SSH-tunneled database connections and multi-environment deployments 
  • Prior experience mentoring or leading a small team 

Tech Stack 

  • Python 
  • Pandas 
  • TensorFlow
  • Hugging Face Transformers
  • PostgreSQL 
  • SQLAlchemy 
  • Wallaroo ·
  • Paramiko/SFTP 
  • openpyxl/xlrd
  • REST APIs
  • OAuth2/JWT 

Why This Role 

You will have high autonomy over a system that directly impacts how financial data flows through RealPage's platform. The ML models you build will reduce manual data mapping for enterprise property management clients, and the pipelines you maintain process real financial documents daily. This is not a research role — it is applied ML engineering where your models ship to production and your code runs against real client data. As a Staff Engineer, you will shape the technical direction of the platform and have meaningful influence over how the team grows. 

SALARY AND BENEFITS

  • RealPage provides a competitive salary package along with a comprehensive benefit plan that includes:
  • Health, dental, and vision insurance.
  • Retirement savings plan with company match.
  • Paid time off and holidays.
  • Professional development opportunities.
  • Performance-based bonus based on position.

Compensation may vary depending on your location, qualifications including job-related education, training, experience, licensure, and certification, that could result at a level outside of these ranges. Certain roles are eligible for additional rewards, including annual bonus, and sales incentives depending on the terms of the applicable plan and role as well as individual performance.

Equal Opportunity Employer: RealPage Company is an equal opportunity employer and committed to creating an inclusive environment for all employees.


USD $107,200.00 - USD $182,600.00 /Yr.

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