Related skills
python distributed systems ci/cd apis knowledge graphsπ Description
- Design, implement, and maintain production AI services for NLQ workflows.
- Evaluate NLQ accuracy using precision/recall and semantic checks.
- Build automated evaluation pipelines and CI/CD tests.
- Design semantic models and knowledge graphs to improve NL answers.
- Analyze NLQ failures; create error taxonomies, instrumentation, logging.
- Develop and expose APIs for NLQ services and semantic layers.
π― Requirements
- Strong software engineering building production systems (Python, APIs, distributed).
- Experience evaluating NLQ/LLM systems, including precision/recall.
- Hands-on designing automated test frameworks and evaluation pipelines.
- Cloud-native architectures, CI/CD, and production deployment of AI systems.
- Knowledge of semantic modeling, ontologies, or knowledge graphs.
- Design scalable, reliable systems bridging AI models and data.
π Benefits
- Equal opportunity employer; diverse and inclusive workforce.
- Background checks may be required after offer.
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