1

Amazon Data Annotation Jobs in Seattle, WA (NOW HIRING)

next page

Showing results 1-20

Amazon Data Annotation information

How much do Amazon data annotation jobs pay?

Amazon data annotation jobs typically pay between $12 and $20 per hour, depending on experience, location, and task complexity. These roles often require attention to detail and familiarity with annotation tools, and may offer flexible schedules for remote work.

What are the key skills and qualifications needed to thrive in the Amazon Data Annotation position, and why are they important?

To thrive as an Amazon Data Annotation specialist, you need keen attention to detail, accuracy, and proficiency in data labeling or annotation, often supported by a background in data entry or related fields. Familiarity with annotation tools, Amazon’s proprietary data platforms, and in some cases basic understanding of programming languages or machine learning concepts is beneficial. Strong communication skills, adaptability, and the ability to work independently or with minimal supervision help individuals excel in the role. These abilities are crucial for ensuring high-quality, reliable data that supports Amazon’s AI and machine learning initiatives.

What is an Amazon Data Annotation job?

An Amazon Data Annotation job involves labeling or tagging data such as text, images, audio, or videos to improve machine learning models. Annotators follow specific guidelines to provide accurate labels that help refine Amazon's AI systems, including Alexa and product recommendations. This work is often detail-oriented and may require understanding context, language nuances, or specific industry knowledge. The role can be full-time or contract-based and may involve remote or on-site work, depending on the project.

Does Amazon really pay you to work from home?

Amazon Data Annotation jobs are typically remote positions that pay employees for their work from home. Compensation varies based on the role and hours worked, and employees are usually paid through direct deposit on a regular schedule. These jobs often require attention to detail and familiarity with annotation tools.

What does a typical day look like for an Amazon Data Annotation specialist?

A typical day as an Amazon Data Annotation specialist involves reviewing, labeling, and annotating diverse datasets, such as images, videos, or text, using specialized software and following detailed guidelines. You may collaborate with team members or project leads to clarify instructions and ensure consistency across annotations. Periodic quality checks and feedback sessions are common, helping you refine your work and maintain high standards. While much of the work is independent, clear communication and responsiveness are important for meeting project deadlines and successfully supporting Amazon’s AI development goals.

What is annotation in Amazon?

In the context of Amazon data annotation jobs, annotation involves labeling or tagging data such as images, videos, or text to help train machine learning models. Workers use specialized tools to add accurate labels, which are essential for improving AI systems' performance. Attention to detail and understanding of the data are important for this role.

Does data annotation actually pay well?

Data annotation jobs, including roles like Amazon Data Annotation, typically offer hourly wages that are close to minimum wage or slightly above, depending on the employer and location. Pay rates can vary based on the complexity of tasks, required skills, and whether the work is freelance or full-time, but generally do not provide high salaries. Many positions are suitable for entry-level workers and may include flexible schedules or remote work options.
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 Amazon Data Annotation jobs in Seattle, WA? For Amazon Data Annotation jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Amazon Data Annotation jobs in Seattle, WA look for? The top searched job categories for Amazon Data Annotation jobs in Seattle, WA are:
Infographic showing various Amazon Data Annotation job openings in Seattle, WA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Senior Software Engineer, AI for the Planet

$126K - $189K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago


Job description

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.Our base salary range is $126,000 - $189,000 and in addition we have generous bonus plans to provide a competitive compensation package.Who We Are:

We are a small engineering team at the Allen Institute for AI working on AI for the Planet. We're working on maritime conservation, food security, disaster resilience, and climate solutions with some of the most impactful organizations on the planet. We work very closely alongside a ML research team and our Product & Partnerships teams, focused on building products that support our environmental and high-impact users.

Today, our team works on two products:

Skylight uses AI to detect illegal, unreported, and unregulated fishing in real time. Governments, enforcement agencies, and conservation organizations in 95+ countries use it to protect their waters. Our advanced AI-powered platform delivers real-time vessel detections and actionable insights that empower enforcement agencies globally to protect marine ecosystems. Read more at https://allenai.org/skylight. 

OlmoEarth is an open, end-to-end platform built around our family of foundation models for Earth observation. The OlmoEarth Platform enables our users to create custom fine-tuned models to detect and classify novel geospatial features. The platform handles the full loop: imagery acquisition from Sentinel-1, Sentinel-2, and Landsat; annotation; distributed training and inference; and a viewer so the outputs are usable by people who aren't ML experts. Partners today include NASA JPL (wildfire risk), IFPRI (crop mapping in Kenya), Global Mangrove Watch, and the Amazon Conservation Alliance. Read more at https://allenai.org/olmoearth. 

If you're the kind of engineer who gets energized by building technology that helps protect oceans, forests, and the climate, who wants to move fast, work across disciplines, and see your code have real-world impact, this is for you.

What We Believe:

The mission is the point. We're building AI for the planet: environmental conservation, food security, climate. If it's important to you to work on problems with a positive impact on our planet and the world, you're in the right place. 

The engineer closest to the user makes the best decisions. We put weight on talking to users, sitting with partnerships, and working side by side with researchers. You can't ship the right thing if you don't understand who you're shipping it for. This engineering team travels regularly to meet with users. 

Iterate small. Our users are tackling huge problems: illegal fishing, food security, climate resilience. They need tools that genuinely help. We believe the fastest way to build those tools is to design and build alongside them as partners: ship something functional, learn from how they use it, and iterate from there. Keeping users in the loop is how we build a better product, faster.

We ship high-quality code quickly, and we learn fast from mistakes. We hold a high bar for what we put into production, but we also move with urgency. When something breaks, we focus on understanding the system, not blaming individuals. Failures are signals that help us strengthen the layers that protect our users.

In-person matters. A lot of the best work on this team happens in unscheduled hallway conversations between engineering, research, and partnerships. We're in the office most days because that's where the team is at its best.

We hire for curiosity. The technologies we use will change over the years, and the engineers who do well here are the ones who enjoy learning new things, not the ones who've memorized a particular toolkit.

Ideas get better when they're challenged. We make decisions by talking them through - asking questions, pushing back when something doesn't quite add up, and being open to changing our minds. Everyone here is still learning, and we like it that way.

Who You Are: 

We're looking for a strong builder. Someone with deep experience shipping high-quality, scalable, full-stack products that integrate state-of-the-art ML models. Someone who wants to grow alongside a team working at the forefront of applied AI, on a product that exists to do good in the world. A great candidate is someone who thoughtfully reflects on our internal processes and is comfortable pushing for change.

Required Qualifications:

  • 5+ years of professional software engineering experience in industry. Internships, graduate school, and research positions are valuable but do not count toward this.
  • Experience working as a generalist software engineer across multiple parts of the stack and product lifecycle. Strong foundations in web applications, data pipelines, distributed systems, and modern cloud tooling. The specific frameworks matter less than demonstrated ability to pick up new technologies as the field evolves.
  • You're using modern AI tooling (e.g. Claude Code, agentic workflows) to move faster and rethink how engineering gets done.
  • A track record of taking software products end to end. Shaping requirements, designing architecture, shipping to external users, and continuing to develop them over time based on user feedback.
  • Ownership overproduction systems. Including taking on-call rotations, troubleshooting production issues, and digging into logs, metrics, and code to develop real, actionable insight when something needs attention.
  • You write clear technical plans, give and receive feedback well, constantly prioritize, and can guide stakeholders through the details.
Preferred qualifications:
  • Experience at small or growth-stage companies, where you own outcomes end to end without heavy process scaffolding.
  • Hands-on experience integrating machine learning models into production systems: deployment, monitoring, scaling real-time inference, and iteration. You collaborated directly with researchers to bring models out of a research context, and you built user-facing applications where AI outputs need to be communicated clearly to non-technical users. 
  • You're opinionated about software engineering practice: coding patterns, breaking down work, code review, testing, build systems. You bring that judgment to the team while staying open to other perspectives.
  • A demonstrated track record of technical depth and self-directed learning - for example: open-source contributions, technical writing, conference talks, sustained side projects.
  • Open to occasional international travel to meet directly with the people using what we build.
Projects We're Excited About:

To give you a better idea of the kinds of projects we work on, here are some examples of our current and past  projects:

  • Automated model development: We're building the OlmoEarth Platform to enable users to go from raw tabular data to a fine-tuned, evaluated, production-ready computer vision model, without needing an ML engineer. The underlying infrastructure allows us to run jobs across thousands of parallel GPUs and terabytes of satellite imagery - covering continent-sized areas for fractions of a penny per square kilometer. We're also pushing into agentic approaches: agents that help with dataset discovery, preparation, and augmentation, and agents that explore model configurations and architectures to find the right setup for a given use case.
  • Deploy multi-tenant agents: We are building a multi-tenant agent-orchestration platform to power Skylight's next generation of AI products - starting with Shippy, our maritime-domain-awareness agent. Every end user gets their own isolated sandbox: a per-user container stack with persistent GCS-backed state, a conversation history, and a hardened network boundary where the agent runtime can run free, in a secure environment. This platform will allow us to launch agentic-powered products without re-inventing the wheel every time. 
  • Sentinel-2 vessel detections: We use the Sentinel-2 Satellites from the European Space Agency to detect locations of vessels globally in near-real-time. Our data-pipelines download imagery as soon as it's available and run our state-of-the-art computer vision models to detect vessels and make these observations available to our users, typically in under 4 hours from an image being taken. You can read more about this project in our blog post here.
Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

  • Must be able to remain in a stationary position for long periods of time. 
  • The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. 
  • The ability to observe details at close range.
  • Can work under deadlines.
A Little More About Ai2:

Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world's biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.

In addition to Ai2's core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

  • We are a learning organization - because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
  • We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
  • We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
  • We emphasize a healthy work/life balance - we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
  • We are collaborative and transparent - we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
  • We are in Seattle - and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
  • We are friendly- chances are you will like every one of the 200+ (and growing) people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits: 

  • Team members and their families are covered by medical, dental, vision, and an employee assistance program.
  • Team members are able to enroll in our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
  • Team members are able to enroll in our company's 401k plan.
  • Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
  • Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
  • Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assign...