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Freelance Machine Learning Data Annotation Jobs in Seattle, WA

Unchain Data

Machine Learning Engineer

Bellevue, WA · On-site

$161.14 - $200/hr

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core ... Data Analysis and Insight Generation : Analyze experimental data to extract actionable insights.

PitchBook Data

Machine Learning Engineer

Seattle, WA

This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing ...

Expedia

Senior Machine Learning Scientist

Seattle, WA · Remote

$104K - $142K/yr

Our Machine Learning and Data Science team is growing. We are looking for a Senior Machine Learning Scientist to help tackle some of the most complex customer experience problems in the travel domain.

Apple Inc.

Machine Learning Engineer

Seattle, WA · On-site

$175 - $308.50/hr

Seattle, Washington, United States Machine Learning and AI Our team delivers algorithms that power ... We are actively involved in the whole ML cycle from data collection design and data processing to ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Collaborate with data scientists and flight software engineers to integrate AI capabilities into ... Proven experience deploying machine learning models into production. * Strong software engineering ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$95 - $135/hr

Collaborate with data scientists and flight software engineers to integrate AI capabilities into ... Proven experience deploying machine learning models into production. * Strong software engineering ...

Unitytech

Machine Learning Engineer

Bellevue, WA · On-site +1

$117K - $152K/yr

... machine learning pipelines, and business operations ... As data volume and complexity grow, our platform enables large-scale model training, feature ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in Seattle, WA

Freelance Machine Learning Data Annotation information

See Seattle, WA salary details

$14

$24

$39

How much do freelance machine learning data annotation jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for freelance machine learning data annotation in Seattle, WA is $24.89, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $28.46 per hour, depending on experience, location, and employer.

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 Seattle, WA?

The most popular types of Machine Learning Data Annotation jobs in Seattle, WA are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Seattle, WA?

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

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

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Seattle, WA are:

Freelance Machine Learning Data Annotation jobs near you

Machine Learning Engineer - Computer Vision & Data Systems

Socket.dev

Seattle, WA • On-site

$140 - $200/hr

Other

Posted 13 days ago

Job description

At Apple, we are dedicated to creating technologies that enrich people's lives. Our teams develop products and experiences that empower millions of users globally, by combining world-class engineering with a deep commitment to innovation, quality, and privacy. We are seeking a Machine Learning Engineer with strong expertise in computer vision and large-scale data processing. In this role, you will contribute to the development of next-generation real-time sensing and data intelligence systems by designing algorithms, building scalable data pipelines, and collaborating with multi-functional teams to deliver high-impact, production-quality solutions.

DESCRIPTION
  • Design, build, and maintain large-scale data processing workflows, ensuring efficiency, scalability, and reliability across diverse data sources and modalities.
  • Develop and optimize computer vision models that power core product experiences, including areas such as image understanding, multi-view geometry, 3D reconstruction, and visual recognition.
  • Partner closely with engineering, research, and data teams to translate product requirements into technical solutions. This includes prototyping models, running large-scale experiments, improving data quality, and ensuring seamless integration of algorithms into production systems.
  • Explore emerging areas such as LLM-based agents, retrieval-augmented systems, and tool-oriented reasoning to improve internal workflows or data operations.
MINIMUM QUALIFICATIONS
  • Strong foundation in computer vision, including experience with deep learning–based vision models and at least one area such as detection, segmentation, 3D vision, geometric methods, tracking, or self-supervised learning.
  • Hands-on experience developing machine learning models using frameworks such as PyTorch or TensorFlow.
  • Experience building or optimizing large-scale data pipelines (e.g., distributed ETL, dataset generation, annotation workflows, data validation, or high-throughput processing).
  • Proficiency in Python or C++ for algorithm development and data processing.
  • Experience working with distributed computing frameworks (e.g., Spark, Ray, or equivalent).
PREFERRED QUALIFICATIONS
  • PhD in a relevant field with research directly related to computer vision, large-scale data systems, or multimodal learning.
  • Experience designing or evaluating agentic systems, including LLM-powered tools, RAG pipelines, or automated data reasoning workflows.
  • Familiarity with prompt engineering, tool-use patterns, and LLM model behavior.
  • Experience deploying ML models at scale, including monitoring, evaluation, and continuous improvement.
  • Knowledge of data quality assessment, dataset curation methodologies, and evaluation frameworks.
  • Experience with GPU-based optimization, large-batch training, or distributed training.
  • Strong multi-functional collaboration skills and the ability to lead technical initiatives.
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