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Freelance Machine Learning Data Annotation Jobs in Texas

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

... Annotation * Data Interpretation * Fact Checking * Independent Research * Problem-Solving * Attention to Detail Preferred Qualifications * 3+ years of experience in Data Science, Machine Learning ...

Develop computer-language subroutines, scripts, and programs that support automated or semi-automated data analysis, annotation, and characterization. * Apply appropriate machine learning and ...

Data Annotator

Irving, TX · On-site

$109K - $132K/yr

... data annotation and quality assurance (QA) review for perception and VLA (Vision-Language-Action) data, including video, images, and multi-sensor machine data. - Annotate mining site entities (e.g ...

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Freelance Machine Learning Data Annotation information

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Texas?

The most popular types of Machine Learning Data Annotation jobs in Texas are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Texas?

For Freelance Machine Learning Data Annotation jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Texas look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Texas are:

What cities in Texas are hiring for Freelance Machine Learning Data Annotation jobs?

Cities in Texas with the most Freelance Machine Learning Data Annotation job openings:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Machine Learning Data Scientist

Socket.dev

Houston, TX • On-site

$102 - $156.40/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago


Key responsibilities

  • Support the development, delivery, and continuous improvement of forecasting processes and models for ENGIE's U.S. power supply business.

  • Validate forecast inputs and outputs, monitor model performance, and ensure forecast quality and model drift are maintained over time.

  • Build, implement, and refine forecasting models and tools, ensuring operational reliability and alignment with business needs.


Job description

Senior Machine Learning Data Scientist

Location: Houston, United States, 77056

Company: ENGIE North America Inc.

Business Unit: Supply & Energy Management

Division: BP B2B US

Employment Type: Permanent, Full-Time

What You Can Expect

As our Senior Machine Learning Data Scientist, you will support the development, delivery, and continuous improvement of forecasting processes and models for ENGIE's U.S. power supply business. Working under the guidance of the Portfolio & Load Analytics Manager, you will collaborate closely with portfolio managers, risk, IT, and other stakeholders to ensure forecasting outputs are accurate, timely, and aligned with operational needs.

In this role, you will leverage rigorous data collection, validation, and analysis to improve forecast performance and support portfolio management, hedging strategies, and risk management activities across U.S. power markets.

Position is based in Houston, TX, and reports to the Portfolio & Load Analytics Manager.

  • You will be actively involved in the design, implementation, and continuous improvement of forecasting tools, models, and methodologies, while helping build a modern forecasting platform for the US power market. Your role will include validating forecast inputs and outputs, monitoring model performance from a data science standpoint, and ensuring model drift and forecast quality remain under control over time. You will also work cross-functionally within the broader forecasting community and with forecasting teams in other countries to promote knowledge sharing, consistency, and the cross-pollination of ideas and best practices.
  • You will be responsible not only for the technical development of forecasting solutions, but also for ensuring their operational reliability and relevance to business needs. This includes building models across the full lifecycle—from feature engineering, training, tuning, and execution to validation, monitoring, and ongoing refinement—while maintaining strong software engineering standards that deliver dependable, production‑grade forecasts. Because these forecasts are used to support commercial decisions across ENGIE's U.S. power business, reliability, traceability, and robustness are essential parts of the role.
  • In addition to model development, you will provide scientific expertise for bespoke analyses and contribute to the continuous improvement of forecasting practices, performance measurement, and platform capabilities. A strong understanding of forecasting methodology, model governance, and production‑quality software development is essential to succeed in this role, along with the ability to translate complex analytical outputs into practical business value for stakeholders across the organization.
What You'll Bring
  • You hold a Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Finance, or Economics, or a related field. In lieu of a degree, we will consider a combination of relevant experience that demonstrates strong quantitative rigor and practical business acumen.
  • You have the technical expertise to build, analyze, and productionize forecasting models, along with the communication skills needed to align diverse stakeholders around a clear and informed point of view.
  • Minimum of five (5) years of experience building and deploying forecasting models and data pipelines using Python and SQL, with ownership of production deliverables.
  • You have a strong foundation in probability, statistics, data science, and machine learning, with practical experience in time series forecasting.
  • You have advanced proficiency in Python, SQL, Git, and modern data platforms such as Databricks and Spark, with the ability to build scalable data pipelines and automate workflows.
  • You are knowledgeable in developing and deploying forecasting models, including regression, time series, and machine learning techniques, with experience improving forecast accuracy and backcasting performance.
  • You have experience designing and maintaining end‑to‑end forecasting systems including data ingestion, feature engineering, model training, hyperparameter tuning, deployment, and performance monitoring.
  • You are knowledgeable in energy markets, load forecasting, or commodity trading, and understand how market dynamics and regulatory changes impact forecasting outputs.
  • You are an effective communicator who can translate complex analytical insights into clear recommendations for both technical and non‑technical stakeholders, including portfolio managers, traders, and risk teams.
  • You have strong analytical and problem‑solving skills, with the ability to manage multiple priorities, work independently, and deliver accurate, high‑quality results in a fast‑paced environment.
Additional Details
  • Role is eligible for our hybrid work policy.
  • Must be willing and able to comply with all ENGIE ethics and safety policies.
Compensation

Salary Range: $102,000 - $156,400 USD annually.

This represents the average expected pay range for a qualified candidate.

ENGIE complies with all federal, state, and local minimum wage laws. Actual salary offered may vary depending on geography, experience, education, internal pay alignment, or other bona fide factors.

In addition to base pay, this position is eligible for a competitive bonus / incentive plan.

Benefits

Our comprehensive benefits package includes options for medical, dental, vision, life insurance, employer‑paid short‑term and long‑term disability insurance, ESPP, generous paid time off including wellness days, holidays and leave programs. We also help you plan for retirement by offering a 401(k) Retirement Savings Plan with a company match. These benefits support your well‑being and that of your family at all stages of life.

Equal Opportunity

ENGIE North America is an equal opportunity employer and is firmly committed to creating an inclusive workplace for all employees. We are committed to providing employees with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status.

If you need assistance with this application or a reasonable accommodation due to a disability, you may contact us at ENGIENA-ENGIEHR@engie.com. This email address is reserved for individuals with disabilities in need of assistance and is not a means of inquiry regarding positions or application status.

We are unable to sponsor or take over sponsorship of an employment visa for this role at any time.

The safety of our employees is our number one priority. All employees at ENGIE have both a duty and the authority to STOP WORK if unsafe acts are observed.

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