Project specification
Project expertise
Description
For a digitalization project in a corporate environment, we are looking for an experienced ML Engineer. The focus is on building fully automated conversational evaluation processes, intent detection, and professional context engineering for our customer's AI assistant.
- Evaluation of the AI assistant as well as individual tools and agents in terms of quality, robustness, and user experience
- Building and further developing intent detection (including VA forwarding, PBK detection)
- Structured dialogue analysis to derive reliable insights from user conversations (conversational design)
- Context engineering: structuring, connecting, and maintaining extensive knowledge sources for consulting services
- Optimizing latency and costs through flexible model selection and orchestration
- Designing, building, and operating automated end-to-end ML pipelines for evaluation and monitoring
Requirements
Solid ML fundamentals with practical experience in building, operating, and deploying production LLM systems, especially scalable high-throughput inference.
Experience in automating end-to-end production ML systems: pipeline deployment, Docker containerization, reproducible environments, cloud monitoring/scaling, and infrastructure as code.
Practical experience in building and orchestrating data pipelines with Apache Airflow (DAGs) as well as automating recurring data/ML processes.
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