Qualcomm seeks a Software Test Engineer to validate on-device AI solutions across mobile, PC, and automotive platforms, with emphasis on generative AI models (LLMs, LVMs, LoRA, agentic workflows) and system-level performance across SoC components (CPU, GPU, DSP, NPU). The role involves designing end-to-end validation workflows, developing test automation frameworks in Python/Java/Shell, analyzing model outputs for accuracy and robustness, and conducting stability and performance testing.… Candidates should have 1–3+ years of software testing or AI validation experience (or be fresh graduates with strong AI/ML fundamentals), proficiency in Python, Java, and Linux, and solid understanding of AI inference, RAG systems, and multi-step reasoning pipelines.
lora jobs in San Diego
Staff/Sr. Staff Software Engineer role focused on AI inference optimization on Snapdragon platforms, including model optimization, quantization, graph transformations, and runtime execution for LLMs, LVMs, and LMMs.… You will design and implement graph lowering and optimization techniques within ONNX Runtime, ExecuTorch, and Qualcomm AI Stack SDK, working across ML algorithms, inference systems, and hardware integration. The role requires 6–8+ years of software development experience, 3+ years in AI/ML inference or model optimization, deep expertise in Python and C/C++, PyTorch/ONNX, and transformer architectures. You will mentor junior engineers, drive features end-to-end, and collaborate across ML Research, hardware, product, and QA teams.
Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers.… Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.