As the leader in digital olfaction, Aryballe combines biochemical sensors, advanced optics, and machine learning in a single objective solution to collect, display and analyze odor data using our Cloud Storage and SaaS tools. Aryballe is seeking a Machine-Learning OPS Engineer to join our growing team.
As MLOps engineer, you are the bridge between R&D and production. The primary focus for this role is to set up the right tools, infrastructures, and processes to take advantage of the algorithms created by the data science team and to facilitate integration into the software product. This role is not involved in the design of Machine Learning algorithms, but rather in their rewriting / assembling and integration in a cleaner and clearer way for their effective production and deployment.
This role will have strong collaboration between the Data and software teams, along with DevOps, to ensure a productive ecosystem.
- Master’s degree in engineering
- 2-5 years’ experience in machine learning ops or a similar role in the biotech and/or IoT field
- Good technical knowledge and understanding of Machine-learning environment/framework
- Experience in a software productization environment with understanding on how to communicate between R&D and Product Development / Management
- Technical stack: Python, Pytorch, Tensorflow, Beam, Cloud provider, Dockers, CI/CD
- Upper intermediate (level B1+/B2) English Required
- Fluency in French is not mandatory but a plus
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