Voice AI Systems Test Engineer

About the job

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Systems Test Engineering General Summary: Job Overview Join Qualcomm’s Multimedia Systems Group as a Voice AI Systems Test Engineer, responsible for end-to-end validation of Voice AI features, Model evaluation, and quality KPIs sign-off for on-device Voice AI features for next-generation multimedia platforms. In this role, you will focus on validation, benchmarking, data-driven evaluation, competitive analysis of Always-On AI and Agentic AI voice use cases, which includes ASR, TTS, multilingual translation, and intelligent voice assistants. Your work will ensure that Qualcomm’s Voice AI solutions meet and exceed market expectations by matching or outperforming reference implementations and competing solutions across performance, quality, latency, power, and robustness. Responsibilities Voice AI Validation & System Testing • Perform system-level validation and testing of Voice AI features, with emphasis on Always-On AI and Agentic AI use cases. • Design, execute, and maintain comprehensive test plans for Voice AI pipelines including ASR, TTS, NLP, Translation, Summarization, and Language Models. • Validate functional correctness, latency, power, memory, and long-run stability of Voice AI systems on embedded hardware (NPU, GPU, CPU). • Maintain Performance dashboard to detect regressions, identify quality gaps, and predict performance trends across releases. Performance, Quality & Competitive Benchmarking • Compare performance and perceptual quality of Qualcomm Voice AI solutions against internal reference implementations, customer baselines, and competing open-source solutions in the market. • Conduct objective and subjective quality analysis for Voice AI features (accuracy, intelligibility, naturalness, latency perception, robustness). • Drive validation with the goal to meet and beat market expectations, using measurable KPIs and user-experience metrics. • Perform competitive benchmarking of open-source and proprietary models from a system-level quality and performance standpoint. Hardware Acceleration & System Integration Validation • Validate HW AI acceleration paths, ensuring correct and efficient offload across NPU, GPU, CPU, and DSP. • Evaluate end-to-end voice AI pipelines, which includes low power modes, and realtime inference behavior in batch mode and streaming mode. • Verify correct interaction across application, framework, DSP, and hardware layers. Automation, Debug & Cross-Team Collaboration • Develop and maintain automated test suites, regression frameworks, and evaluation pipelines for Voice AI and Agentic AI workflows. • Analyze logs, traces, metrics, and dumps to perform root-cause analysis of functional, performance, or quality issues. • Collaborate closely with R&D, Systems, Platform, Product, and Customer teams to drive fixes, improvements, and release readiness. • Document test methodologies, KPIs, validation results, and competitive insights for internal and external stakeholders. Requirements • Strong programming and scripting skills in C/C++ and Python, with focus on test automation, data analysis, and evaluation tooling. • Experience in system-level testing and validation of ML or AI workloads on embedded platforms. • Solid understanding of Voice AI domains: ASR, TTS, NLP, multilingual translation, and voice assistants. • Hands-on experience validating ML inference performance and quality on NPU/GPU/CPU. • Working knowledge of deep learning frameworks such as PyTorch, TensorFlow, ONNX from a testing and inference evaluation perspective. • Understanding of ML architectures (Transformers, LSTM, GRU, diffusion models) for validation, benchmarking, and analysis. • Experience validating model quantization, compression, and hardware acceleration techniques. • Strong debugging skills for embedded systems, DSP pipelines, and AI accelerators. • Experience with AI-assisted test data analysis, model-based evaluation, and KPI-driven benchmarking is a strong plus. • Excellent communication and collaboration skills to work across global, cross-disciplinary teams. Behavioral & Professional Expectations • Strong quality and customer-experience mindset with attention to detail. • Self-driven engineer capable of handling complex system-level validation challenges. • Ability to translate test data and metrics into actionable insights. • Excellent verbal and written communication for clear reporting and cross-team alignment. • Team player who collaborates effectively with R&D, platform, and product organizations. • Commitment to engineering excellence, continuous learning, and innovation. • Actively supports diversity and inclusion within the team and company.