Job Description
- Packaging and deploying machine learning models to production systems
- Optimizing the performance of ML systems across the stack
- Working with a wide range of different data sources: text, images, video, audio, voice, and tabular
- Building voice streaming, processing, packet capture systems
- Building and maintaining pipelines that run ML models online or batch
- Training models
- Some of the technologies you might stumble upon in existing projects: fastAPI, TensorFlow, sklearn, numpy, Airflow, Kubernetes, Keras, PyTorch, Kaldi, MLFlow, Docker
Requirements
- 2+ years of hands-on experience working with back-end and database technologies
- Experience with the Python data science stack
- Flexibility to work on different projects
- Having lots of curiosity and an eye for details
- Excellent written and verbal English communication skills
Company offers
- Frequent team events
- Highly varying projects – you won’t be stuck on a single project for 3-5 years
- Flexibility
- A lot of freedom to choose the tools and methods to get the job done
- Sport compensation
- Competitive salary
