Agile Remote Operator, GO-AI

Are you ready to shape the future of robotics through human-AI collaboration? Join us in a role where your judgment and adaptability directly impact how Amazon's robotic systems learn and evolve. You'll work at the intersection of artificial intelligence and robotics, helping define how machines understand the world through your expert data annotations, remote tele-planning, and real-time operational support. This isn't traditional data labeling. You will collaborate with scientists and engineers on ambiguous, cutting-edge projects where standard procedures don't yet exist, and your insights will help create them.

Key job responsibilities

• Perform multi-modal data annotations including object segmentation, classification, written descriptions, and detection for robotics and AI model training
• Collaborate with scientists and engineers to translate ambiguous technical requirements into clear annotation standards and standard operating procedures (SOPs)
• Conduct remote tele-planning and tele-operation activities to support robotics systems development and testing
• Define quality standards and key performance indicators (KPIs) for annotation projects where established procedures do not yet exist
• Validate annotated data using troubleshooting techniques and validation scripts to ensure accuracy and consistency
• Analyze the relationship between ground truth data quality and AI model performance metrics such as accuracy, precision, and false positive rates
• Identify process gaps and improvement opportunities, then implement proactive measures to maintain high-quality output
• Communicate project status, challenges, and recommendations to technical teams and stakeholders through written reports and presentations
• Travel to the United States approximately 1-2 times per year for one week per trip A day in the life Your day starts reviewing new robotics tasks requiring annotation standards built from scratch. You'll collaborate with research scientists via video calls to understand model requirements, then design annotation approaches and quality metrics. Mid-morning, you might annotate complex robotic manipulation scenarios across video, image, or text data-providing the foundation that trains autonomous systems. Afternoons involve analyzing quality trends, identifying improvements, and documenting best practices for future scale. You'll alternate between focused annotation work on multi-modal data and collaborative problem-solving sessions where your expertise shapes next-generation AI robotics. The variety keeps every day engaging, with direct impact on robotic systems deployed across Amazon's network. About the team Amazon Robotics develops state-of-the-art robotics for Amazon's Fulfillment Network, which handles more individual items than any company in the world. We develop autonomously driving mobile robots and complex manipulation robots to solve real-world problems at scale. Within Amazon Robotics, the Global Operations - Artificial Intelligence (GO-AI) team enables Amazon to accelerate and scale our robotic and automation solutions through human supervisory control. We partner across Amazon's World Wide Operations organization to deliver data annotation services, ground truth data, and operational support that powers AI innovation. Our team thrives on solving ambiguous challenges, building processes where none exist, and maintaining the highest quality standards. We value curiosity, collaboration, and the ability to translate complex technical requirements into actionable workflows. As we expand our capabilities in remote operations and AI training, you'll help define what success looks like for this emerging field.

Basic qualifications

- Experience supporting Windows, Mac and/or Linux operating systems in a corporate setting

- Experience dealing well with ambiguity, prioritizing needs, and delivering measurable results in an agile environment

- Bachelor's Degree in Computer Science, Engineering, or related technical field, OR 3+ years of professional experience in data annotation, AI/machine learning support, or robotics operations

- 2+ years of experience collaborating with science or engineering teams to define dataset requirements for training AI models and converting those requirements into standard operating procedures

- 2+ years of experience performing multi-modal data annotations including object segmentation, classification, written description, and detection

- 1+ years of experience defining quality standards and KPIs for data annotation projects

- Experience with basic technical tools including Excel, reporting tools, and shell scripts

- Demonstrated written and verbal communication skills in English, including the ability to deliver presentations to technical audiences

Preferred qualifications

- Master's degree or above in Computer Science, Engineering, or related fields

- Experience demonstrating problem solving and root cause analysis

- Experience with remote tele-planning or tele-operation of robotic systems

- Experience working with industry data labeling tools such as Computer Vision Annotation Tool (CVAT), Labelbox, or SageMaker Ground Truth

- Familiarity with manipulation robotics and mobile robotic systems

- Understanding of testing methodologies such as A/B testing for dataset validation and performance evaluation

- Experience configuring and using open-source tools to improve or validate ground truth data quality

- Experience managing relationships with senior technical stakeholders across multiple teams

- Track record of working independently with minimal direction in fast-paced, rapidly changing environments

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.