Device Driver Engineer

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is looking for an Embedded SW Engineer to develop the firmware for our Edge AI processors. The candidate must possess an excellent understanding of computer architecture and operating system concepts including, but not limited to, memory management, virtualization and PCIe address space. The role includes designing and developing the core Firmware for various parts of the SOC. The candidate must possess strong communication skills to interface with Runtime, Architecture and H/W teams. Responsibilities Develop the critical pieces of EAI Firmware used to deploy inference jobs on EAI processors Validate different IP blocks on the SOC Evaluate and integrate third-party device drivers to interface with EnCharge’s SW stack Work closely with the Runtime, Hardware and Architecture teams define the driver architecture Qualifications Bachelors in EE/CS Advanced programming skills in C/C++ for operating system kernel & systems development Understanding of RISC-V architecture is a plus Exposure to PCIe BAR and IOMMU architecture Exposure to virtualization and hypervisor technologies Deep understanding of operating systems concepts, data structures, x86-64 and accelerator architectures Experience with low-level debug tools as well as emulators and simulators Experience running, analyzing, and tuning system performance benchmarks Excellent verb

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. About the Role EnCharge AI is seeking an AI Runtime Engineer to develop and optimize the execution stack for our next-generation AI accelerator. In this role, you will work on low-latency, high-performance runtime software that enables efficient execution of deep learning models on specialized hardware. You will collaborate with hardware, compiler, and AI framework teams to deliver optimized AI inference and training performance across cloud and edge environments. Responsibilities Develop and optimize the AI runtime software stack for executing deep learning workloads on AI accelerators. Implement task scheduling, memory management, and kernel execution strategies for efficient computation. Optimize data movement between host and device using PCIe, DMA, shared memory. Design and implement high-performance APIs for AI Inference frameworks such as OpenVino, ONNX Runtime, vLLM Work on graph execution optimizations, including kernel fusion, pipelining, tensor tiling, and caching. Integrate runtime components with AI compilers (LLVM, MLIR, XLA, TVM) for optimized execution. Ensure scalability and reliability of the AI runtime for cloud-based and edge AI deployments. Qualifications Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 3+ years of experience in developing low-level runtime software for AI accelerators, GPUs, or