NVIDIA Off Campus Drive 2024 Hiring Freshers As SWQA Test Developer Intern Role- Apply Now

The incumbent will be working on helping us to build tools/utility/framework in Python/C++/C which would help automate and optimize the testing workflows in Embedded domain. The candidate will be mainly working on ACE (Avatar Cloud Engine) and DeepStream SDK for inference workflows and associated microservices/apps. The new intern will be guided by a Sr. Engineer and the output produced can also be used for their credentials towards the internship work done, back in college (after getting the necessary NDA/Approvals from the organization).

What you’ll be doing:

• Understand and design a test framework to validate avatar cloud engine workflows and intelligent video analytics applications, define apps/workflows configuration and perform deployment of complete stack, and automate the process using Nvidia’s Test framework.
• Define test procedures based on functional and test design specifications of IVA or inference Applications.
• Write python-based scripts, write unit tests, execute cloud scenarios, provide detailed technical analysis, prioritize the issue, and drive the action, publish weekly status report.
• Should be confident to give good technical presentations and work for continuous test framework improvement.
• Deploy the test framework in Kubernetes / Helm environments.

What we need to see:

• Pursuing a degree course in computer science/electronics/telecommunication with strong academics.
• Good Communication skills (interpersonal and across teams).
• Excellent analytical and problem-solving skills.
• Very organized, proactive, and has good learning ability.
• Languages – Python/C/C++.
• Strong in OOPs concepts and Data structures.
• Knowledge of Linux, AI/ML/DL, message broker like Kafka Tools, Spark, Elasticsearch, Logstash, and Kibana.
• Knowledge of cloud architecture viz. AWS, Azure, etc. and Helm/K8 deployments.
• Knowledge of SQL/NoSQL Database management tools.

Ways to stand out from the crowd:

• Any certification course on Machine learning.
• Knowledge of deployment technologies like Kubernetes.