Lead and drive innovative projects related to automatic structuring and understanding of unstructured content for our projects

Design efficient deep learning-based solutions and ensure high-quality deliverables

Refactor, extend, and improve Contaminant ID's model, algorithms, and MLOps so as to follow best practices and increase its autonomy as a product

Update dependencies and replace OSS libraries that cannot be commercialized, containerize the solution, and help set up CI/CD pipelines

Improve NFR aspects of the solution, such as security and modularity, and consult with the original developers of the prototype solution to productize it

At least 3 years of industry experience as a Machine Learning Engineer with a focus on scientific research, experimentation, and optimal design

Strong proficiency in TensorFlow/Python servers, JavaScript for web portal, Tableau for reporting, MariaDB for data storage, Filesystem for video storage, and Docker/Kubernetes for deployment

Proven experience in refactoring or rewriting parts of existing Python/TensorFlow code, updating dependencies and replacing OSS libraries that cannot be commercialized, containerizing the solution, and setting up CI/CD pipelines

Familiarity with NFR aspects of a solution, such as security and modularity, and ability to improve them

Ability to document the new code design and comment on the implementation

B2+ English level

Familiarity with AWS, Terraform, and Ansible

Experience with GPU acceleration and parallel computing

Familiarity with Natural Language Processing (NLP) techniques