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Remote Amazon Data Annotation Jobs in Seattle, WA

... remote environment Nice to Have * Master's degree or PhD in Machine Learning, Computer Science, Engineering, or a related field * Prior experience with data annotation, data quality assurance, or AI ...

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Remote Amazon Data Annotation information

What is the difference between Remote Amazon Data Annotation vs Remote Mechanical Turk Worker?

AspectRemote Amazon Data AnnotationRemote Mechanical Turk Worker
CredentialsNo formal certifications required, but attention to detail helpsNo formal certifications required, basic task understanding needed
Work EnvironmentRemote, flexible hours, online platformRemote, flexible hours, online micro-task platform
Employer & IndustryAmazon, e-commerce, AI training dataVarious clients, data labeling, surveys, research

Remote Amazon Data Annotation involves labeling data specifically for Amazon's AI and e-commerce needs, often requiring attention to detail. Mechanical Turk workers perform a variety of micro-tasks across industries. While both are remote and flexible, data annotation is more specialized for AI training, whereas Mechanical Turk offers broader task types.

What are some common challenges faced by Remote Amazon Data Annotation specialists and how can they be addressed?

Remote Amazon Data Annotation specialists often encounter challenges such as maintaining consistency and accuracy across large volumes of data, managing repetitive tasks, and staying engaged while working independently. To address these, it's important to develop a strong attention to detail, utilize quality control tools provided by the platform, and take regular breaks to minimize fatigue. Additionally, staying connected with your team through regular check-ins and feedback sessions can help ensure alignment on annotation guidelines and improve overall performance.

What are Remote Amazon Data Annotation jobs?

Remote Amazon Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, or audio to help train machine learning models used by Amazon. Employees work from home using specialized tools to ensure accuracy and consistency in the data provided. These roles often require attention to detail, the ability to follow guidelines, and sometimes specific domain knowledge depending on the project. Data annotation is essential for improving the performance of AI systems in tasks like product recommendations, voice recognition, and search algorithms. These roles may be full-time, part-time, or project-based, offering flexibility for remote workers.

What are the key skills and qualifications needed to thrive as a Remote Amazon Data Annotation Specialist, and why are they important?

To thrive as a Remote Amazon Data Annotation Specialist, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a high school diploma or relevant experience. Competence with web-based annotation tools, cloud-based platforms, and sometimes Amazon-specific data systems is typically required. Diligence, consistency, effective communication, and the ability to work independently are valuable soft skills in this role. These skills and qualities are important to ensure high-quality, accurate data labeling that supports effective machine learning and AI model development.
What are the most commonly searched types of Amazon Data Annotation jobs in Seattle, WA? The most popular types of Amazon Data Annotation jobs in Seattle, WA are:
What are popular job titles related to Remote Amazon Data Annotation jobs in Seattle, WA? For Remote Amazon Data Annotation jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Remote Amazon Data Annotation jobs in Seattle, WA look for? The top searched job categories for Remote Amazon Data Annotation jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Remote Amazon Data Annotation jobs? Cities near Seattle, WA with the most Remote Amazon Data Annotation job openings:

Senior C# Full-Stack Engineer - AI Data & Infrastructure

Alignerr

Seattle, WA โ€ข Remote

Other

Posted 5 days ago


Job description

Senior C# Full-Stack Engineer - AI Data & Infrastructure
About the Role
What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior C# Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on every day.
This is a fully remote contract role with meaningful technical depth and real production impact. You'll work alongside data, research, and engineering teams at the frontier of AI development - solving hard problems at scale.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 20-40 hours/week
What You'll Do
  • Design, build, and optimize high-performance C# systems supporting AI data pipelines and evaluation workflows
  • Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
  • Improve reliability, performance, and safety across existing C# codebases
  • Collaborate with data, research, and engineering teams to support model training and evaluation workflows
  • Identify bottlenecks and edge cases in data and system behavior - then implement scalable, production-ready fixes
  • Participate in synchronous design and code reviews to iterate on system architecture and implementation decisions
Who You Are
  • Native or fluent English speaker with clear written and verbal communication skills
  • Experienced full-stack developer with a strong systems programming background
  • 3-5+ years of professional experience writing production C# with a focus on modern standards
  • Deep understanding of performance optimization, concurrency (threading, atomics), and memory safety
  • Self-directed and reliable - able to commit 20-40 hours per week and deliver without hand-holding
Nice to Have
  • Prior experience with data annotation, data quality, or evaluation systems
  • Familiarity with AI/ML workflows, model training, or benchmarking pipelines
  • Experience with distributed systems or developer tooling
  • Background in C++17/C++20 or other systems-level languages
Why Join Us
  • Work on real production systems used by leading AI research labs
  • Fully remote - work from anywhere, on a schedule that suits you
  • Freelance autonomy with the structure of impactful, technically demanding work
  • Contribute to infrastructure that directly influences how next-generation AI models are built and evaluated
  • Potential for ongoing work and contract extension as new projects launch