Machine Learning Engineer (ASR)

About the Role: We're looking for an experienced Machine Learning Engineer to join our AI team. You'll bridge the gap between research and engineering, implementing and deploying state-of-the-art ASR solutions while maintaining high engineering standards.

• Implement, benchmark 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


• Ensure continuous training for models on production


• Design and conduct experiments to validate new approaches, datasets, and architectures


• Build and maintain data pipelines and audio preprocessing workflows


• Improve and ensure company follow best MLOps practices

Required Qualifications:

• Master’s degree in Computer Science, Engineering, or a related technical field or equivalent industry experience


• 8 years of experience in ML engineering or relevant fields


• Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow)


• Experience with deep learning models, including transformers


• Experience with MLOps pipeline implementation and maintenance (Docker, MLflow, W&B, DVC, Kubernetes)

Highly Valued:

• Direct experience with ASR models (e.g., Whisper, wav2vec, HuBERT) and speech/audio processing pipelines


• Experience working with multimodal data (e.g., audio text, audio video)


• Demonstrated research experience (publications, research projects, or industrial research)


• A hands-on mindset and willingness to engage with meticulous data-related tasks


• Experience with distributed training systems

Nice to Have:

• NLP experience


• Open-source contributions


• Experience in a startup-like environment

• Attractive compensation aligned with your skills


• Flexible work arrangements


• Professional development allowance

If you're passionate about Machine Learing and want to work with cutting-edge technologies, we'd love to hear from you!

Location: Hamburg Employment Type: Full-time