| Área de la Empresa | Tecnologías de Información |
| Cargo Solicitado | Otros empleos |
| Puestos Vacantes | 1 |
| Tipo de Contratación | Tiempo completo |
| Nivel de Experiencia | Sin experiencia |
| Salario máximo (USD) | |
| Salario minimo (USD) | |
| Vehículo | Indiferente |
| País | Costa Rica |
| Departamento | Otro |
Description
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
- 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 t
| Informática | Sistemas Requerido |
Universidad Completa | Graduado |
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