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Freelance Machine Learning Data Annotation Jobs in Seattle, WA

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 ...

Emonics LLC

Machine Learning Engineer

Seattle, WA · On-site

This is an excellent opportunity for someone who wants to build practical machine learning solutions, work with real-world data, and develop their skills across the machine learning lifecycle. Key ...

New

Grid

Machine Learning Engineer

Seattle, WA · On-site

$120K - $140K/yr

Perform data research and analysis using Grid's proprietary dataset as well as other relevant ... Proven experience in Machine Learning and/or Applied Science, including a strong background in ...

Kindredventures

Machine Learning Engineer

Seattle, WA · On-site

$125 - $150/hr

Perform data research and analysis using Grid's proprietary dataset as well as other relevant ... Proven experience in Machine Learning and/or Applied Science, including a strong background in ...

Posted today

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

Perform data research and analysis using Grid's proprietary dataset as well as other relevant ... Proven experience in Machine Learning and/or Applied Science, including a strong background in ...

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

$100 - $125/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 ...

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 ...

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.

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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 Sep 7, 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

Senior Manager, Machine Learning Engineering

Metropolis

Seattle, WA • On-site

$200K - $250K/yr

Full-time

Medical, Life, Retirement

Re-posted 11 days ago

Job description

Who we are
The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy - a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn't coming; it's here, and we need builders, innovators and problem solvers to help us create it.
Who you are
Metropolis is seeking a Senior Manager of Machine Learning Engineering within the Advanced Technologies Group to lead the technical vision and execution of our foundational systems that power our next generation of AI. You will oversee 4 critical pillars within the Machine Learning org:data engineering, annotation pipelines, ML Infrastructure and Deployment of Agentic AI solutions. You are a hands-on, senior technical leader with a broad dynamic range, capable of providing high-level strategic direction while remaining technically proficient enough to dive into the weeds with your team. Your mission is to transition state-of-art models into robust, autonomous production systems that automate complex enterprise workflows.You will partner closely with internal engineering teams and external vendors to build the scalable tools and data pipelines that define the future of recognition economy.
What you'll do
  • Build and maintain scalable, compliant and auditable data infrastructure to serve computer vision and AI pricing use cases
  • Build scalable data engineering pipelines and automated annotation workflows (LLM-in-the-loop) to reduce reliance on manual labeling and accelerate model iteration
  • Own the MLOps lifecycle, including distributed training infrastructure, model registries, and low-latency inference services. Ensure high availability and observability for all deployed models
  • Define technical direction, lead and grow a high-performance team of data and ML infrastructure engineers to influence impactful business outcomes
  • Develop foundational systems to productionize agentic AI, Large Language Models (LLMs) and Vision Language Models (VLMs) solutions for workflow automation to enhance our products
  • Enable Metropolis's move into personalization and targeted advertisement through innovative ML data pipelines and feature stores
  • Collaborate with external vendors and annotation platform providers to ensure high-quality data for production models
  • Partner with other ML leaders (Growth , Edge deployment) and cross-functional leaders in Hardware, Platform, and Product engineering to align development roadmaps
What we're looking for
  • 10+ years of professional experience in data and machine learning engineering with proven expertise in building enterprise-scale, auditable ETL pipelines and data governance mechanisms
  • 5+ years of experience in leadership and management, ideally having managed other managers
  • MS or PhD in computer science and/or a quantitative discipline
  • Strong experience in distributed data processing like Apache Spark, Kafka, Cloud native data storage and processing services
  • 1+ years experience building data /eval pipelines and deploying agentic AI solutions (LLMs and/or VLMs)
  • Experience managing technical programs, defining milestones, and communicating progress to diverse audiences
  • Familiarity with deep learning frameworks such as TensorFlow or PyTorch
  • Strong proficiency with SQL and Python
  • Engage effectively with external data providers and vendors
  • Familiarity with computer vision systems and models (e.g. object detection, tracking, segmentation)
While not required, these are a plus:
  • Manage large scale datasets and database tools for data processing
  • Deploy ML services to the cloud with a focus on scalability and reliability
  • Operate in innovative, high-growth environments

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection
When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis's total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Onsite
Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate's application relative to the required job qualifications and responsibilities listed in the job posting.
As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.
Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

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