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Nice to have requirements
— Building and improving our engineering infrastructure to enable and scale our applied
algorithmic research and development. On a day to day, some of your responsibilities will
— Design, Develop, Test, and Maintain ETLs and services for integrating with our
customer’s various data systems.
— Design, Develop, Test, and Maintain ETLs and services for building our own data
processes to accommodate applied research needs as well as production needs.
— Finding performance bottlenecks in our data pipelines and our machine learning
pipelines and resolving them
— Develop end-to-end algorithmic solutions for complex ML problems — from research and
training models, through design, development, evaluation, and optimization.
— Develop train and inference engine pipelines in a large-scale distributed system.
— Transform NLP and data-related ML/DL algorithmic approaches into efficient and
optimized production-ready solutions.
— Design, Implement and Optimize ML/DL and research pipelines to improve the algorithm’s
— Transform high-level product requirements into technical requirements
— Brainstorm and prototype algorithmic improvements.
— Work in an ambiguous environment and collect requirements from different personas in
the company (Product, FE, Research, etc.)
— Advise and collaborate with researchers on DL software engineering aspects (such as
tools and practices)
Our client implements Artificial Intelligence innovations in medical coding. They believe that medical coding should become fully automated and they know how to help this to happen.