Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
The intern will work on revamping existing feature pipelines and building of new feature pipelines via feature engineering efforts. The intern can also be involved in the deployment of models via a systematic MLOps pipeline. By analyzing the output of the deployed models, the intern will also perform further analysis to better improve the models. Throughout the process, the intern will learn the skills of proper documentation for these works.
Requirements:
Creative and innovative mindset and ability to work independently
Ability to use one or more development language (Python, SQL, Dbt, etc)
Familiar with cloud technologies (Amazon Web Services, Google Cloud Platform)
Familiar with orchestration tools.
Interest and experience in Data Science, Machine Learning and Artificial Intelligence
Learning Objectives
The intern can learn data science concept, feature engineering skills, deployment of AI/ML models systematically via MLOps and understand the wider realm of data science. The application of the different cloud computing knowledge can also be picked up.
Learning Outcome
Industry practices and essentials to writing clean code in Python
Industry usage of a proper CI/CD for code repository integration and deployment
Feature engineering, including pipeline design and boiler plating
Algorithm selection and AI/ML model training
AI/ML model evaluation techniques
Cloud computing technology – AWS
Infrastructure as code - Terraform
Technical requirement gathering and translation
Are you game?