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Applied AI Scientist(m/f/d)

CompraTica Empleos

EMP:Technology
Berlin
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usNET CHECK GmbH was founded in 1999 with the aim of improving the quality of communication networks

Since then, NET CHECK has developed into the leading partner of network operators and infrastructure providers of mobile and fixed networks of all technologies.

Its core competencies include international network benchmarking (comparative measurements) as well as network planning and fault analysis.

NET CHECK has one of Germany's largest crowdsourcing platforms, which generates over 144 million data points every day.

Our commitment to quality and security has earned us the trust of scientific and government institutions.

NET CHECK is headquartered in Berlin and is part of the NC GROUP, an owner-managed group of companies with a total of over 180 employees at five locations in Germany and one in Belgrade, Serbia.

 Job Summary: We build AI platforms that transform complex telecom network data—including drive tests, voice quality, broadband diagnostics, and signaling analysis—into clear, actionable insights.

We are looking for an Applied AI Scientist who combines strong analytical thinking with practical engineering.

Habilidades

You will model complex problems, develop and prototype ML and agentic AI solutions, and turn them into reliable, production-ready tools for real users while applying the latest developments in AI.

ResponsibilitiesDesign and build agentic AI systems and RAG pipelines that can reason over technical documentation and live network data.

Take ownership of testing and evaluation by developing evaluation datasets, metrics, and benchmarks for accuracy, retrieval quality, latency, and cost.

  • Ensure system quality can be measured reliably and regressions are identified before reaching users.
  • Develop and continuously improve our evaluation and observability practices, including offline and online evaluations, LLM-as-a-judge approaches where appropriate, regression testing, and quality dashboards for agentic AI and RAG systems.

Turn data science insights into.

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