Fine-tune, evaluate, and deploy state-of-the-art models in speech recognition and audio processing
Collect and curate custom ASR datasets, including data sourcing, annotation pipeline setup, quality control, and alignment/segmentation procedures
Build and maintain robust data pipelines and audio preprocessing workflows for clinical environments
Work closely with the MLOps team to ensure continuous training, monitoring, and seamless deployment of models in production
Design and conduct experiments to validate new approaches, datasets, and architectures to improve accuracy in noisy or specialized medical settings
Collaborate with product managers and developers to translate complex speech solutions into production-ready healthcare tools

Master’s degree in Computer Science or Engineering
5-8+ years of experience in ML engineering
Strong programming skills in Python
Experience with ML frameworks (PyTorch, TensorFlow or Jax)
Direct experience with ASR models (Whisper, wav2vec, …)
Extensive experience with transformer-based architectures and deep learning models
Practical experience with MLOps pipeline components such as Docker, MLflow, W&B, DVC, or Kubernetes
Knowledge of multilingual or domain-specific modeling (specifically medical, legal, or other specialized terminologies) (nice to have)
Experience with distributed training systems for large-scale model optimization (nice to have)
Full proficiency in English and German.

Senior Machine Learning Engineer – ASR

Key skills