You will help design and build the next iteration of processes to improve quality of Place attributes employing machine learning.
You will maintain up-to-date knowledge of research activities in the general fields of machine learning and LLMs.
Utilize machine learning algorithms / LLMs to generate translation / transliterations, standardization / derivation rules, extract place attributes such as name, address, category and hours of operations from web sites using web scraping solutions.
Participate in both algorithm and software developments as a part of a scrum team, and contribute artifacts (software, white-paper, datasets) for project reviews and demos.
Collaborate with internal and external team members (researchers and engineers) on expertly implementing the new features to the products or enhancing the existing features. With end-to-tend aspects like developing, testing, and deploying.
Who are you?
You are determined and have the following to be successful in the role :
MS or PhD in a discipline such as Statistics, Applied Mathematics, Computer Science, Data Science, or others with an emphasis or thesis work on one or more of the following areas : statistics / science / engineering, data analysis, machine learning, LLMs
2+ years of experience in Data Science field.
Proficient with at least one of the deep learning frameworks like Tensorflow, Keras and Pytorch.
Programming experience with Python, shell script
Applied statistics or experimentation (. A / B testing, root cause analysis, etc)
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