AWS Rekognition Subject Matter Expert (SME)

Location : REMOTE
Duration 12 months

Flexible Hours Working

Key Responsibilities
Architect, configure, and manage Amazon Rekognition facial recognition services for high-performance use cases.
Build and integrate Rekognition features into REST-based APIs supporting facial detection, matching, and metadata tagging.
Develop and maintain Rekognition collections, including: collection creation, update, and deletion; bulk user/image ingestion using S3 URIs; metadata tagging and tracking of usage metrics.
Implement facial tagging workflows with capabilities to: detect faces and return bounding boxes; match faces to known users and return confidence scores; identify unmatched or unknown faces; manage multiple image associations per user.
Support automated and manual feedback loops, including retraining triggers and tagging corrections.
Collaborate with front-end developers to build lightweight tools for testing and validation of facial recognition endpoints.
Implement and enforce secure API access, including key management, role-based permissions, and usage logging.
Optimize Rekognition performance for large-scale image libraries, supporting both real-time and batch tagging processes.
Monitor system usage and recommend improvements to cost-efficiency, accuracy thresholds, and scalability.
Contribute to technical documentation, deployment scripts, and system architecture artifacts.
Required Qualifications
Minimum of 5 years of hands-on experience with Amazon Rekognition, including facial comparison, detection, and collection management.
Strong background in RESTful API development, AWS S3, IAM, and cloud-based image workflows.
Proven experience with high-volume image processing and tagging systems.
Proficiency with JSON over HTTP and modern API design patterns.
Understanding of facial recognition metadata standards, model confidence scoring, and tagging automation.
Familiarity with secure API integration, usage logging, and error handling frameworks.
Ability to work within Agile or DevSecOps teams, contributing to fast-paced, iterative development environments.
Preferred Qualifications
Experience with multi-face detection and spatial tagging, including row or position-based face ordering.
Experience with observability platforms like Datadog, AWS CloudWatch, or similar tools.
Familiarity with user access management, API gateway integration, and scalable microservice environments.
Prior experience supporting photo management, publishing, education, or media platforms is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Location : REMOTE
Duration 12 months

Flexible Hours Working

Key Responsibilities
Architect, configure, and manage Amazon Rekognition facial recognition services for high-performance use cases.
Build and integrate Rekognition features into REST-based APIs supporting facial detection, matching, and metadata tagging.
Develop and maintain Rekognition collections, including: collection creation, update, and deletion; bulk user/image ingestion using S3 URIs; metadata tagging and tracking of usage metrics.
Implement facial tagging workflows with capabilities to: detect faces and return bounding boxes; match faces to known users and return confidence scores; identify unmatched or unknown faces; manage multiple image associations per user.
Support automated and manual feedback loops, including retraining triggers and tagging corrections.
Collaborate with front-end developers to build lightweight tools for testing and validation of facial recognition endpoints.
Implement and enforce secure API access, including key management, role-based permissions, and usage logging.
Optimize Rekognition performance for large-scale image libraries, supporting both real-time and batch tagging processes.
Monitor system usage and recommend improvements to cost-efficiency, accuracy thresholds, and scalability.
Contribute to technical documentation, deployment scripts, and system architecture artifacts.
Required Qualifications
Minimum of 5 years of hands-on experience with Amazon Rekognition, including facial comparison, detection, and collection management.
Strong background in RESTful API development, AWS S3, IAM, and cloud-based image workflows.
Proven experience with high-volume image processing and tagging systems.
Proficiency with JSON over HTTP and modern API design patterns.
Understanding of facial recognition metadata standards, model confidence scoring, and tagging automation.
Familiarity with secure API integration, usage logging, and error handling frameworks.
Ability to work within Agile or DevSecOps teams, contributing to fast-paced, iterative development environments.
Preferred Qualifications
Experience with multi-face detection and spatial tagging, including row or position-based face ordering.
Experience with observability platforms like Datadog, AWS CloudWatch, or similar tools.
Familiarity with user access management, API gateway integration, and scalable microservice environments.
Prior experience supporting photo management, publishing, education, or media platforms is a plus.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.