Software QA Test Developer - Embedded

Role Overview

We are seeking a skilled Software QA Test Developer to join our test development team passionate about Conversational AI products. In this role, you will own quality for NVIDIA's voice AI pipelines — end-to-end systems integrating ASR, LLM, and TTS models built on open-source frameworks and NVIDIA NIM microservices. You will compose test strategies, build AI-powered test automation, and drive CI pipeline reliability across multi-model, multi-agent voice systems deployed on cloud, workstation, and edge targets.

Responsibilities

• Develop and sustain CI/CD pipelines for voice agent projects, automating build, deploy, and test workflows across cloud and GPU deployment profiles.
• Develop Python-based test frameworks to validate cascaded voice pipelines (ASR, LLM, TTS), including latency, accuracy, and interruption-handling scenarios.
• Track and improve code coverage across Conversational AI codebases; identify gaps and add targeted unit, integration, and end-to-end tests.
• Build and complete test plans for multi-agent orchestration, tool-calling workflows, and multimodal (audio/video/image) understanding features.
• Evaluate and benchmark Conversational AI models for accuracy, efficiency, and latency using project evaluation frameworks.
• Develop AI agents and LLM-powered workflows to automate repetitive QA tasks such as log analysis, regression triage, and test-case generation.
• Identify, document, and regress bugs across the full stack — from containerized deployments and NIM microservices to the frontend client.
• Collaborate with engineering and release teams to review feature requirements, specifications, and technical build documents.

Requirements

• B.Tech. or M.Tech. or equivalent degree in CS/CE/IT/ECE/EEE.
• 2+ years of hands-on testing experience in software/embedded systems.
• Strong programming skills in Python; ability to write test frameworks and automation scripts from scratch.
• Proficiency in Linux environments, shell scripting, and command-line debugging.
• Hands-on experience with LLMs and Conversational AI systems (ASR, TTS, or NLP pipelines).
• Proven experience developing or collaborating with AI Agents and agentic workflows (e.g., LangChain, Pipecat, or comparable frameworks).
• Experience crafting and maintaining CI/CD pipelines (GitHub Actions, Jenkins, or similar) and managing daily automation tasks.
• Strong understanding of QA processes — code coverage tracking, test planning, regression management, and bug lifecycle.
• Working knowledge of Docker, Docker Compose, and container-based deployments.

Skills

• Python
• LLM
• Docker
• CI/CD
• Linux

Nice to Have

• Experience testing real-time streaming or voice/audio pipelines.
• Experience with NVIDIA NIM microservices, NGC, or GPU-accelerated inference.
• Hands-on with Kubernetes or edge deployment platforms (Jetson, DGX Spark).
• Any degree/certification in Machine Learning or Artificial Intelligence.