Exciting Job Alert! Join NVIDIA as a Software QA Test Developer Engineer 2024

Introduction

Imagine being at the leaders of artificial intelligence innovation, collaborating with NVIDIA, one of the world’s most recognizable tech companies. AI applications are revolutionizing industries, and NVIDIA’s pioneering AI-driven solutions are at the forefront. There is currently an excellent opportunity for a talented Software QA Test Developer Engineer to join NVIDIA’s Embedded QA team in Pune and contribute to ground-breaking work on AI workflows and microservices.

Table of Contents

This great opportunity that post for you, Harry, apply now.

Why Choose NVIDIA?

NVIDIA is at the forefront of AI, cloud, and computer technology, continually pushing the boundaries. For engineers looking to establish a name for themselves in AI, NVIDIA provides an unparalleled environment for innovation and growth.

Position Details

Location: Pune, India
Team: Embedded QA Group
In this position, you’ll join NVIDIA’s dedicated team focused on ensuring the reliability and quality of AI-driven applications. The role emphasizes testing cloud-native microservices, a crucial component in fast-tracking vision AI applications.

Purpose of the Role

This role is critical to NVIDIA’s vision AI operations, where developers create and deploy solutions based on powerful NVIDIA GPUs and Jetson Orin edge AI platforms. This role entails testing multiple microservices and applications and validating each level of the development pipeline.

Apply Here: Software QA Test Developer Engineer

Job Designation: Software QA Test Developer Engineer
Salary: 7-14 LPA
Qualification: B.E/B.Tech
Experience: 0-2 Years
Organization Name: NVIDIA
Website: PayPal
Locations: Pune, India
Mode: Offline

Key Skills and Experience Required

Creating test scenarios for AI workflows
As a Software QA Test Developer Engineer, your key responsibilities will be to design and code robust test cases. You will work on a variety of video analytics applications, including multi-camera AI and real-time tracking systems.
Creating and Validating Analytics Configurations
You will configure analytics, deploy test environments, and ensure that all elements are validated. Your contribution will improve the stability of NVIDIA’s AI platforms across the pre-deployment and post-deployment phases.
Developing detailed test plans and cases
With a strong client focus, you’ll create test strategies that meet specific objectives while maintaining high standards. These plans will contain test cases to ensure full QA coverage of NVIDIA’s vision AI applications.
Collaborating with cross-functional teams.
The role calls for close collaboration with project management, hardware teams, and software developers. You will actively engage in product reviews by providing comments on specs and technical designs.
Analyzing and reporting bugs.
Maintaining quality is essential in this profession. You’ll document and analyze bugs, periodically publishing reports and sharing data insights with stakeholders. This feedback loop will drive continuous improvements in NVIDIA’s AI systems.

Specific Projects and Use-Cases

Multicamera Tracking Systems
A critical use case is multi-camera tracking, which enables seamless monitoring and surveillance across several camera feeds.
AI-powered Network Video Recorders (NVRs)
These NVRs use artificial intelligence to deliver extensive analytics and monitoring capabilities, making them ideal for high-security situations and data centers.
Occupancy Heatmaps
Occupancy heatmaps provide useful insights on how places are used, with uses ranging from retail to urban planning.

Essential Technical Skills for the Role

Python proficiency
Python programming is vital because it allows engineers to build and execute tests from scratch while adhering to NVIDIA’s strict quality standards.
Debugging and Troubleshooting
Excellent debugging skills are critical for discovering and addressing difficulties in AI workflows and apps. Engineers are expected to evaluate logs properly in order to identify root causes.

Technical Tools and Software

Docker, Container, and Kubernetes
Working with Docker and Kubernetes is critical for deploying and managing microservices environments. This guarantees that the testing procedure is both effective and adaptive.

Qualifications Required

Education: A B.Tech. degree or equivalent in CS, CE, IT, ECE, or EEE.
Experience: 1–2 years in Embedded Software Validation, with a strong preference for experience in AI and video analytics.

Standout Skills for Success in This Role

Understanding of Generative AI and AI-powered microservices
Expertise in generative AI, huge language models, and microservices gives candidates an advantage. Experience with AI animation and 3D graphics is also beneficial.
Knowledge of Advanced Tools.
Candidates who are proficient in Kafka, Spark, and Elasticsearch will stand out because these tools are critical in NVIDIA’s data-intensive environment.

Growth Opportunities at NVIDIA

NVIDIA is known for nurturing talent and providing ample learning opportunities. Engineers in this role will gain exposure to cutting-edge AI and machine learning technologies, with the chance to grow their careers in a leading AI company.

Apply now!

Apply now! Please check the link in the “apply now section” to learn more about this position and submit your application.

Conclusion

This position at NVIDIA in Pune is ideal for software QA engineers who are passionate about AI, cloud-native technologies, and testing. With NVIDIA’s commitment to innovation, the Software QA Test Developer Engineer will play an important role in improving AI applications and guaranteeing quality.

FAQs

1. What is the role of a Software QA Test Developer Engineer?
The role involves designing and executing test cases for NVIDIA’s vision AI applications, validating cloud-native microservices, and ensuring the quality of AI workflows.

2. What experience is needed for this position?
Candidates should have 1-2 years of experience in Embedded Software Validation, particularly in the field of AI and video analytics.

3. What technical skills are required?
Proficiency in Python, Docker, containers, Kubernetes, and debugging skills are essential.

4. Why should I consider working at NVIDIA?
NVIDIA offers a unique environment at the forefront of AI innovation, providing ample growth and learning opportunities.

5. How do I apply for the role?
You can apply by visiting the official job posting on NVIDIA’s website and submitting your application through the link provided.