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Role description
We are seeking an AI Testing Engineer to validate and assure quality of AI/ML systems powering real-time contextual advertising on live video streams. The role involves testing multi-modal AI outputs (video + text), ensuring accuracy of detected moments, and automating validation workflows.
This role is critical for native moments validation and system-level QA in a real-time streaming environment.
Key Responsibilities
Validate AI-generated outputs against labelled datasets and expected outcomes
Perform content validation for native moments detection across video streams
Design and implement automated testing frameworks (Python-based)
Build validation harness for:
JSON parsing and comparison
Structured output validation using defined schemas
Conduct multi-modal validation (video, audio, transcript outputs)
Execute system integration and end-to-end testing
Track accuracy metrics, defect logging, and root cause analysis
Automate regression and validation pipelines across datasets
Collaborate with Applied Scientists to validate LLM and GenAI outputs
Work within AWS environment using services such as:
S3 (data storage).Lambda (processing).CloudWatch (monitoring)
Required Skills & Experience:
Strong Python scripting for automation and testing . Experience in AI/ML model validation and QA workflows.
Hands-on with: JSON parsing, schema comparison Data validation pipelines
Experience in testing: Multi-modal AI systems (vision + NLP + audio) LLM outputs and generative AI pipelines. Good understanding of: Structured output validation AI accuracy evaluation techniques Familiarity with AWS cloud environment (S3, Lambda, logging/monitoring) Experience with media/video content analysis workflows preferred Ability to handle mixed manual + automated testing approaches
We are seeking an AI Testing Engineer to validate and assure quality of AI/ML systems powering real-time contextual advertising on live video streams. The role involves testing multi-modal AI outputs (video + text), ensuring accuracy of detected moments, and automating validation workflows.
This role is critical for native moments validation and system-level QA in a real-time streaming environment.
Key Responsibilities
Validate AI-generated outputs against labelled datasets and expected outcomes
Perform content validation for native moments detection across video streams
Design and implement automated testing frameworks (Python-based)
Build validation harness for:
JSON parsing and comparison
Structured output validation using defined schemas
Conduct multi-modal validation (video, audio, transcript outputs)
Execute system integration and end-to-end testing
Track accuracy metrics, defect logging, and root cause analysis
Automate regression and validation pipelines across datasets
Collaborate with Applied Scientists to validate LLM and GenAI outputs
Work within AWS environment using services such as:
S3 (data storage).Lambda (processing).CloudWatch (monitoring)
Required Skills & Experience:
Strong Python scripting for automation and testing . Experience in AI/ML model validation and QA workflows.
Hands-on with: JSON parsing, schema comparison Data validation pipelines
Experience in testing: Multi-modal AI systems (vision + NLP + audio) LLM outputs and generative AI pipelines. Good understanding of: Structured output validation AI accuracy evaluation techniques Familiarity with AWS cloud environment (S3, Lambda, logging/monitoring) Experience with media/video content analysis workflows preferred Ability to handle mixed manual + automated testing approaches