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Freelance Machine Learning Data Annotation Jobs in Seattle, WA

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Participate in the full development cycle: data collection, labeling, model development ...

Robinhood

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.

Visa Hunt

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.

Robinhood

Machine Learning Engineer

Bellevue, WA · On-site

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.

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Participate in the full development cycle: data collection, labeling, model development ...

PitchBook Data

Machine Learning Engineer

Seattle, WA · On-site

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 ...

Hive

Machine Learning Engineer

Seattle, WA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... Maintain awareness of industry best practices for data maintenance handling as it relates to your ...

Hive

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... Maintain awareness of industry best practices for data maintenance handling as it relates to your ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

IUNU

Applied Machine Learning Engineer

Seattle, WA · On-site

Responsibilities : • Study and transform data science prototypes • Design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning ...

Sonsoft Inc

C# / Machine Learning

Redmond, WA

Should have at least 1 year of experience in below skills. * C#, data structures, and basic ... Machine Learning, Deep Learning/neural networks. * Data mining. * Azure ML, Cortana Intelligence.

Capital-Group-1

Machine Learning Engineer II

Seattle, WA · On-site

$159 - $255/hr

You successfully research, train, evaluate and deploy models for financial modeling and data ... You have experience solving "full stack" machine learning problems, from data collection and ETL ...

Apple

Machine Learning Engineer

Seattle, WA

$175K - $308K/yr

We are actively involved in the whole ML cycle from data collection design and data processing to ... machine learning or related field PhD in computer vision, computer graphics, machine learning ...

Factspan Inc

Machine Learning Engineer

Seattle, WA

Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying ... Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical ...

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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 Manager

Hive

Seattle, WA • On-site

$180K - $250K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 20 days ago

Job description

About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Machine Learning Manager
In order to execute our vision, we're constantly growing our machine learning team. We are looking for an exceptional leader to help us with that growth, making sure that each engineer reaches their full potential. We value hard workers who have no qualms working with terabyte-scale datasets. We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects of a massive scale, contributes innovative ideas and ingenious modeling improvement strategies to the team, and is capable of mentoring junior engineers through their journey to become better.
Responsibilities
  • Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
  • Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
  • Participate in products technical design and architecture
  • Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production.
  • Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
  • Implement and manage security protocols such as training, code review, and best practices
  • Own and manage the risk and security of your business function in coordination with the Security Team
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements
  • Undergraduate or graduate degree in computer science or similar technical field
  • 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
  • Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
  • 2+ years experience managing machine learning teams
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
  • Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
  • Have experience collaborating with product managers and labeling team in delivering model improvements

Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $180,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.
Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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