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Contract Data Annotation Jobs in Spring, TX (NOW HIRING)

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Contract Data Annotation information

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

What is a contract data annotation job?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

What are the key skills and qualifications needed to thrive as a Contract Data Annotation Specialist, and why are they important?

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.
What are the most commonly searched types of Data Annotation jobs in Spring, TX? The most popular types of Data Annotation jobs in Spring, TX are:
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What cities near Spring, TX are hiring for Contract Data Annotation jobs? Cities near Spring, TX with the most Contract Data Annotation job openings:
Contract Data Annotation jobs near you

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

Lifted, an Upwork Company™

Houston, TX • Remote

$80 - $110/hr

Contractor

Posted 4 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.

    Apply