Posted:5 days ago|
Platform:
Work from Office
Full Time
8+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience in embedded development in C/C++ 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience 5+ years in AI/ML systems and deployment (eg, model deployment, model evaluation, data processing, debugging, fine tuning) Strong understanding of deep learning architectures with emphasis on transformer-based LLMs Proven experience working with edge hardware platforms (Qualcomm, MediaTek, NVIDIA Jetson, Apple Neural Engine, etc) Experience with edge AI inference frameworks (Executorch, TensorFlow Lite, ONNX Runtime, etc) and compiler stacks Experience with GPU programming (eg, CUDA, OpenCL, Metal, Vulkan Compute) Experience with ML frameworks (eg, PyTorch, JAX, TensorFlow) Experience deploying and tuning LLMs using techniques like LoRA, QLoRA, and instruction tuning Strong coding skills in C/C++ and Python to implement custom optimized kernels Performance optimization for inference speed, memory utilization, and bandwidth usage Masters degree in machine learning or equivalent Deep knowledge of SoC architecture, hardware acceleration, vectorization, and memory hierarchies Experience deploying LLMs or advanced ML models on resource-constrained devices Strong Knowledge in the following areas: Generative AI concepts such as embeddings, RAG, semantic search, and transformer-based LLMs MCP workflows and Agentic ecosystem Vector databases (eg, FAISS, Annoy, HNSW) and data pipelines Contributions to open-source inference frameworks or compiler toolchains Strong cross-functional leadership, with the ability to influence product roadmaps and technical strategy across organizations
Amazon
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