Machine Learning Engineer – (Revenue Management & Price Optimization) (m/f/d)

Join a team of ML experts to design and deploy cutting-edge models for price optimization in a production-grade, low-latency service.
Develop regression models to infer optimal bid prices under capacity constraints while capturing demand elasticity and temporal dynamics.
Prototype architectures including deep MLPs, transformer-based models for tabular/sequence data, CNNs for image inputs, and embedding-rich hybrids for accuracy and generalization.
Lead large-scale experimentation and simulations to evaluate model generalization across geographies, seasons, and capacity limits.
Build scalable data and training pipelines using PySpark, Dask, or Polars, with multi-GPU/multi-node setups on AWS; ensure reproducibility and robust deployment.
Implement monitoring, automated retraining, and hyperparameter tuning (Ray Tune, Optuna), while documenting infrastructure and mentoring peers on best practices.