AI and Data Application Intern
Singapore
Razer
Cutting-edge technology✅ Excellent engineering✅ Sustainable✅ Shop Razer's catalogue of headsets, laptops and tech gear for gaming, work and leisure.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.
Job Responsibilities :
Main Tasks & Responsibilities :
Title: AI and Data Application (Intern)
Intern will be playing a pivotal role in building and deploying AI and data applications essential for key business units within the company. The intern will need to have a good software engineering background and be comfortable with working in a cloud environment. This role will challenge the intern into taking up multiple hats thereby increasing the breadth of the intern's capabilities.
Requirements :
- Ability to learn and pick up new technologies fast
- Experience writing Python scripts
- Familiar with calling backend APIs and networking concepts
- Experience with cloud technologies (Amazon Web Services, Google Cloud Platform)
- Knowledge of container services like Docker and Kubernetes
- Familiar with deploying CICD pipelines (GitLab, Jenkins)
- Interest in Generative AI, machine learning and other AI concepts
Learning Objectives and Outcomes
Learning Objectives
The intern can learn to collaborate with a team of expert data scientists, data engineers and machine learning engineers to build industry leading AI products. The intern will be involved in the development phase as well as the CICD phases of these projects.
Learning Outcome
- Industry practices and essentials to writing clean code in Python
- Building robust CI/CD pipelines for continuous code integration and deployment
- Integrating various APIs and software together
- Deploying dockerized solutions on Kubernetes cluster
- SQL database usage of materialized view, view for operations
- Cloud computing technology – AWS
- Infrastructure as code - Terraform
- Technical requirement gathering and translation to end to end delivery of the project
Pre-Requisites :
Are you game?
Tags: APIs AWS CI/CD Docker Engineering GCP Generative AI GitLab Google Cloud Jenkins Kubernetes Machine Learning Pipelines Python SQL Terraform
Perks/benefits: Career development
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