Machine Learning Engineer – (Revenue Management & Price Optimization) (m/f/d)
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The role
You will implement cutting-edge price optimization models in a high-velocity production environment.
Develop regression and advanced architectures (deep MLPs, transformers, embeddings) to infer optimal prices under capacity constraints and changing demand.
Prototype and evaluate models across geographies, seasons, and capacity regimes, with a focus on robustness and transferability.
Design large-scale data pipelines using PySpark, Dask, and Polars, and train with multi-GPU/multi-node setups on AWS.
Establish monitoring, retraining triggers, and automated hyperparameter tuning (Ray Tune, Optuna) for continuous improvement.
Collaborate across data science and infrastructure teams, mentor peers, and document scalable ML production practices.
Develop regression and advanced architectures (deep MLPs, transformers, embeddings) to infer optimal prices under capacity constraints and changing demand.
Prototype and evaluate models across geographies, seasons, and capacity regimes, with a focus on robustness and transferability.
Design large-scale data pipelines using PySpark, Dask, and Polars, and train with multi-GPU/multi-node setups on AWS.
Establish monitoring, retraining triggers, and automated hyperparameter tuning (Ray Tune, Optuna) for continuous improvement.
Collaborate across data science and infrastructure teams, mentor peers, and document scalable ML production practices.
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