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Remote Content Labelling Jobs in Orlando, FL (NOW HIRING)

All JobsContent Labelling JobsRemote Content Labelling JobsRemote Content Labelling Jobs in Orlando, FL

Remote Content Labelling information

See Orlando, FL salary details

$27.5K

$108.9K

$120.4K

How much do remote content labelling jobs pay per year?

As of Aug 16, 2026, the average yearly pay for remote content labelling in Orlando, FL is $108,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,800.00 and $119,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced in remote content labelling roles and how can they be managed?

Remote content labellers often encounter challenges such as maintaining focus during repetitive tasks, managing ambiguous guidelines, and ensuring consistent quality across large datasets. To address these, it's helpful to establish a structured daily routine, actively participate in team discussions or feedback sessions, and utilize available resources for clarification on guidelines. Collaborating with team leads and other labellers through chat platforms also helps in resolving uncertainties efficiently and maintaining high accuracy standards.

What are the key skills and qualifications needed to thrive as a remote content labeller, and why are they important?

To thrive as a Remote Content Labeller, you need strong attention to detail, analytical thinking, and familiarity with content guidelines, typically supported by a high school diploma or equivalent. Experience with content management systems, annotation tools, and sometimes specific training on labeling protocols is often required. Excellent communication, time management, and the ability to work independently are valuable soft skills for this role. These skills ensure accurate and consistent labeling, which is critical for training AI systems and maintaining content quality at scale.

What is remote content labelling?

Remote content labelling is the process of identifying, tagging, or classifying various types of digital content—such as images, videos, text, or audio—from a remote location, typically from home. This work is crucial for training machine learning algorithms and improving artificial intelligence systems, as labelled data helps computers understand and process information. Remote content labellers use specific guidelines and tools provided by their employer or client to ensure consistency and accuracy. The job often requires attention to detail, good communication skills, and the ability to follow instructions closely.

What is the difference between Remote Content Labelling vs Remote Data Annotation?

AspectRemote Content LabellingRemote Data Annotation
Primary FocusLabeling and categorizing content such as images, videos, and text for machine learningAdding detailed annotations to data to improve model accuracy, often including bounding boxes, segmentation, or key points
Skills RequiredAttention to detail, understanding of content types, basic data handlingTechnical skills, familiarity with annotation tools, precision in marking data
Work EnvironmentRemote, flexible hours, often part-time or freelanceRemote, similar flexible setup, often within AI or ML projects

Both roles involve working remotely to prepare data for AI models, but Content Labelling primarily involves categorizing content, while Data Annotation requires detailed technical markings. Understanding these differences helps job seekers find the right fit for their skills and career goals.

What are popular job titles related to Remote Content Labelling jobs in Orlando, FL?

For Remote Content Labelling jobs in Orlando, FL, the most frequently searched job titles are:

What job categories do people searching Remote Content Labelling jobs in Orlando, FL look for?

The top searched job categories for Remote Content Labelling jobs in Orlando, FL are:

What cities near Orlando, FL are hiring for Remote Content Labelling jobs?

Cities near Orlando, FL with the most Remote Content Labelling job openings:

Remote Content Labelling jobs near you
Infographic showing various Remote Content Labelling job openings in Orlando, FL as of August 2026, with employment types broken down into 33% Full Time, 44% Part Time, and 23% Contract. Highlights an 100% Remote job distribution, with an average salary of $108,863 per year, or $52.3 per hour.

Applied Data Scientist

Professional Staffing Services

Orlando, FL • Remote

Contractor

Re-posted 2 days ago

Job description

Applied Data Scientist - Contract to Hire

Location: Florida (Remote but will need to travel to Orlando for your first day, and for occasional meetings and trainings. )

Employment Type: Full-Time, Pay: ~ 100K-150K

Sponsorship: Not Available (Now or in the future)

About The Company

Our client drives innovative, datadriven insights and scalable AI solutions across the entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform audience data into actionable strategies and operational products.

A successful Applied Data Scientist thrives on both analytical creativity and production rigor. As a key member of our client's team, you will own endtoend modeling and deployment work-from the conceptual framing of business problems to data ingestion, model development, and reliable production delivery. Your work will directly shape how our company delivers value to clients and internal stakeholders.

Position Summary & Location Requirements

This is a Florida-based role. While the day-to-day work offers remote flexibility, candidates must reside in the state of Florida and meet the following travel requirements:

  • Day One: Ability to travel to Orlando, FL for your first day/onboarding.
  • Ongoing: Ability to travel to Orlando on occasion for collaborative meetings, trainings, and to support business needs.

Key Responsibilities

In this role, you will bridge the gap between business strategy and technical execution. Specifically, you will:

  • Model & Solution Development: Translate ambiguous business questions into structured analytical and ML solutions. Develop, validate, and optimize models impacting forecasting, segmentation, personalization, recommendation, or operational efficiency.
  • Production & MLOps: Build productionready pipelines and deploy models into scalable environments using robust MLOps practices (CI/CD, automated testing, monitoring), ensuring long-term lifecycle maintenance.
  • Collaboration & Communication: Partner cross-functionally to bridge business requirements and technical design. Communicate insights and technical decisions clearly to both technical and nontechnical stakeholders.
  • Documentation & Standards: Document all models, pipelines, and deployment processes comprehensively to ensure maintainability, reproducibility, and knowledge sharing.
  • Innovation: Stay ahead of emerging tools, techniques, and frameworks in ML/AI to influence best practices across the organization.

Core Qualifications

  • Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Professional Experience: 5+ years of industry experience (excluding internships) in data science and machine learning, including proven ownership of model productization, monitoring, and iterative improvement.
  • Core ML Experience: 3+ years of building machine learning models for business applications (outside of academia), with deep expertise in both supervised and unsupervised learning algorithms.
  • Technical Stack:
  • Python: Strong programming skills with hands-on experience building, training, deploying, and monitoring ML models.
  • SQL: 2+ years of experience with database querying, data preparation, and analysis.
  • Data Warehousing: Working knowledge of large-scale platforms (e.g., Snowflake, SQL Server, BigQuery, Redshift).
  • Cloud Platforms: Familiarity with cloud environments (AWS, Azure, or GCP) and designing end-to-end ML pipelines from ingestion to production serving.
  • Execution Skills: Outstanding analytical skills to diagnose and resolve complex system issues, with a proven ability to manage multiple projects and prioritize tasks effectively.

What Sets You Apart (Preferred Qualifications)

  • Advanced Degree: Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Domain Expertise: Industry experience in entertainment or e-commerce, including domains such as theme parks, hospitality, live performances, ticketing, or retail marketplaces.
  • Advanced ML Architectures: Hands-on experience designing and deploying recommendation models (collaborative filtering, content-based, transformer-based) or working with data labeling, taxonomy design, and classification frameworks.
  • Generative AI: Familiarity with GenAI techniques, language modeling, or frameworks like AWS Bedrock and Hugging Face.
  • Deep MLOps Tooling: Advanced experience with tools like SageMaker, Lambda, Airflow, or MLflow, and the ability to guide architectural/strategic decisions for ML infrastructure.

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