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Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. The company's core technology is the Market Model—a proprietary AI-powered system delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence. Built on a glass-box architecture using market data with full transparency, the technology is deployed across volatile markets including global aviation, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul, delivering an average profit uplift of 7%.
The Large Market Modeling (LMM) team is the engine powering Fetcherr's pricing intelligence. This team builds and trains the models that transform market signals, customer behavior, and competitive dynamics into reliable, production-ready demand models. The LMM team teaches Fetcherr's AI how people buy so it can recommend the right price at the right moment.
As an MLOps Engineer, you will build and maintain the models and data pipelines that power the data science workflows. You'll ensure the accuracy, consistency, and efficiency of data used for model training and inference. This role involves working with both structured and unstructured data from various sources, leveraging expertise in data engineering and machine learning to create a robust, scalable system.
Key responsibilities include: designing and implementing data pipelines for model training and inference; maintaining data quality and consistency across systems; collaborating with data scientists and engineers to optimize model performance; monitoring and troubleshooting production systems; and scaling infrastructure to support growing data volumes and model complexity.
Ideal candidates have relevant experience in data engineering, preferably within AI/ML. Aviation industry experience is a plus but not required.
