1

Data Annotation Research Jobs in Texas (NOW HIRING)

AI, Data Science & Multimodal Research * Apply an AI-first approach to experimental design, data generation, annotation, structuring, and interpretation. * Contribute to development of AI-ready ...

AI, Data Science & Multimodal Research * Apply an AI-first approach to experimental design, data generation, annotation, structuring, and interpretation. * Contribute to development of AI-ready ...

Research Scientist II

Plano, TX · On-site

  • Medical

  • Retirement

AI, Data Science & Multimodal Research * Apply an AI-first approach to experimental design, data generation, annotation, structuring, and interpretation. * Contribute to development of AI-ready ...

Showing results 21-40

Data Annotation Research information

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a data annotation researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.

What are some common challenges faced in data annotation research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

What are popular job titles related to Data Annotation Research jobs in Texas?

For Data Annotation Research jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Data Annotation Research jobs in Texas look for?

The top searched job categories for Data Annotation Research jobs in Texas are:

What cities in Texas are hiring for Data Annotation Research jobs?

Cities in Texas with the most Data Annotation Research job openings:

Copy of CFD & Aerodynamic Engineer (AI Training & Evaluation)

Lifted, an Upwork Company™

Houston, TX • Remote

$80 - $110/hr

Contractor

Posted 19 days ago


Job description

Company Description

An enterprise client is seeking CFD & Aerodynamic Engineers to help train and evaluate next-generation AI systems by contributing real-world engineering expertise.

This opportunity is offered by a leading AI data platform that enables organizations to build intelligent applications powered by high-quality human expertise.

    Job Description

    This opportunity is ideal for experienced CFD and Aerodynamics Engineers who enjoy solving complex engineering problems and want to contribute their expertise to the development of advanced AI systems.

    What You'll Do:

    • Design compact, self-contained CFD and aerodynamics tasks that evaluate AI models' engineering reasoning.
    • Create clear and technically accurate problem statements covering topics such as boundary conditions, mesh quality, flow regimes, and simulation setup.
    • Develop deterministic scoring checkers that objectively evaluate AI-generated responses.
    • Produce verified reference solutions to ensure each task is technically accurate and fully solvable.
    • Review and refine engineering tasks to improve clarity, physical accuracy, and appropriate difficulty.
    • Apply real-world experience with OpenFOAM to develop practical and realistic engineering scenarios.
    • Work independently in a fully remote, asynchronous environment with complete scheduling flexibility.
    Qualifications

    Requirements:

    • Bachelor's degree (or higher) in Aerospace Engineering, Mechanical Engineering, or a closely related discipline.
    • Hands-on experience using OpenFOAM for computational fluid dynamics simulations.
    • Strong foundation in fluid mechanics, aerodynamics, and heat transfer principles.
    • Experience with:
      • Mesh generation
      • Turbulence modeling
      • Boundary condition specification
      • Post-processing and simulation analysis
    • Ability to write clear, precise, and objectively verifiable engineering problems.
    • Excellent written English communication skills with the ability to explain complex technical concepts clearly.
    • Self-motivated, detail-oriented, and able to work independently with minimal supervision.

    Nice to Haves:

    • Experience working on aerospace, automotive, motorsports, renewable energy, or industrial CFD applications.
    • Familiarity with advanced CFD validation and verification techniques.
    • Experience reviewing technical documentation or engineering research.
    • Previous experience contributing to AI, simulation, or data annotation projects.
    Additional Information
    • Fully remote, independent contractor opportunity.
    • Flexible schedule with an expected workload of 10-39 hours per week, depending on project demand.
    • Compensation ranges from $80-$110 USD per hour, based on qualifications and experience.
    • Payments are issued weekly for completed work from the previous week.
    • If selected, you will receive an Upwork contract offer along with onboarding instructions for the client's task platform.
    • To be considered, candidates must:
      • Submit an Upwork proposal.
      • Complete the required Google Form.
      • Accept the Upwork contract to receive onboarding instructions, assessment access, and project payments.
    • Due to the high volume of applicants, only shortlisted candidates will be contacted.