Senior ML/AI Engineer

Clera; Deutschland; Vor Ort; EUR 90.000 - 140.000; Vollzeit

Zusammenfassung

Clera is seeking a senior ML/AI engineer to own and evolve a fast-growing AI-native consumer intelligence platform. You will design, build, and deploy intelligent systems that forecast demand and analyze consumer signals at enterprise scale, shaping product direction and architecture.

You will develop robust ML pipelines, integrate RAG and LLM components, and push the platform toward autonomous decision-making across complex data landscapes, collaborating closely with research and production

Aufgaben

• Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale
• Develop and iterate on the platform's agentic AI architecture—systems that reason across heterogeneous data sources and take autonomous action
• Build and maintain robust ML pipelines: data preprocessing, feature engineering, model training, evaluation, and production deployment
• Architect RAG systems and LLM integrations powering natural language interfaces

Jobbeschreibung

ABOUT THE ROLE

Join a fast-growing, AI-native consumer intelligence platform serving the world's largest retailers and brands. This is a rare opportunity to work at the intersection of cutting-edge AI research and real enterprise deployment — building the intelligent systems at the very core of the product. The platform reasons, forecasts, and acts autonomously across complex enterprise data landscapes, delivering demand forecasting, consumer intelligence, competitive analysis, and autonomous decision-making at scale. You'll be a senior technical owner on a small, high-caliber engineering team, with direct impact on product and architecture decisions.

WHAT YOU'LL DO

• Design, build, and deploy ML models for demand forecasting, time series prediction, consumer sentiment analysis, and anomaly detection at enterprise scale
• Develop and iterate on the platform's agentic AI architecture — building systems that reason across heterogeneous data sources and take autonomous action
• Build and maintain robust ML pipelines: data preprocessing, feature engineering, model training, evaluation, and production deployment
• Architect RAG systems and LLM integrations that power natural language in...