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Tier-1 employer and metro location increase competition, but seniority and niche edge AI skills moderate applicant density.
Strong edge ML, hardware accelerator, and quantization expertise required, limiting cross-industry transferability.
Explicit 9+ years requirement and specialized hardware, LLM, and C++ expertise create strict screening filters.
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Lead development and commercialization of Qualcomm AI Runtime and ML solutions like Snapdragon Neural Processing Engine (SNPE) SDK on Qualcomm SoCs.
Optimize AI/ML stack performance on multiple hardware accelerators (CPU/GPU/NPU) with expert deployment of large C/C++ software stacks.
Continuously update and enhance software and ML solutions based on latest developments in Generative AI and edge-based deployments.
Bachelor's/Master's/PhD in Engineering, Computer Science, or related field.
9-14 years of relevant software development experience, with 1+ year on LLM/Generative AI systems.
Strong programming skills in C/C++ and Python; experience with LLM API testing and providers (e.g., OpenAI, Anthropic).
Understanding of embeddings, vector databases, similarity search, and LLM evaluation frameworks; knowledge of OS concepts, design patterns, and AI hardware accelerator optimization.
Experienced in deploying and optimizing large-scale C/C++ software stacks for AI inference on heterogeneous hardware platforms.
Familiarity with Generative AI models, especially LLMs/Transformers, and the nuances of edge-based AI deployment.
Capable of integrating industry and academic advancements into production ML software for device-level AI inference.