Principal ai/ml software architect

2 weeks ago


Bangalore, India L&T Semiconductor Technologies Full time

Role – Lead/ Principal AI/ML Software Architect Stream - R&D Reporting- Director So C Architecture Position Overview: As an AI/ML software lead / architect you will be responsible for mapping key Machine Learning applications and benchmarks on CPU/NPU/DSPs. We are looking for a dynamic, energetic individuals to join our team. As an ML software stack engineer, you will be responsible for architecting runtime stack, defining the operator mapping and dataflow on cutting edge So Cs. Key Responsibilities : Define software stack that interfaces with open source runtime env like ONNX, Py Torch, Glow compiler Define runtime operator scheduling, memory management, operator dataflow based on tensor residency Propose algorithmic optimization in operators that are mapped to CPU/NPU/DSPs with ONNX / Pytorch / Tensorflow runtime engines to deploy the model on edge So Cs. Use quantization, other techniques to develop efficient models with fast runtimes and minimum load latency. Collaborate with kernel developers to integrate ML operators seamlessly into high level ML frameworks Design and implement C++ runtime wrappers, APIs, and frameworks for ML model execution. Architect optimized CPU alternative implementation for ML operators that are not supported on NPUs Qualifications/ Skills : Masters or Ph D degree in Computer Science, Computer Engineering, Electrical Engineering 12+ years of prior experience in related domain. Detailed and thorough understanding of ONNX / Py Torch / Tensor Flow runtime stack, open source frameworks Strong experience in scheduling operators between NPU CPU and DSPs Experience with graph parsing, operator fusion Strong experience with VLIW instruction set, cache behaviour in CPU Strong experience with managing system memory Detailed understanding of compiler interfacing with runtime stack, JIT compilation flow Strong programming skills in C++, Python. Experience with ML frameworks (e.g., Tensor Flow, Py Torch) is required. Experience with ML models such as CNN, LSTM, LLMs, Diffusion is a must. Experience with ONNX, Pytorch runtime stacks. Knowledge and parallel computing is a bonus. Familiarity with containerization (Docker, Anaconda, etc) is good to have. Motivating leader with good interpersonal skills



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