Must Haves :
- Bachelors degree in electrical engineering, computer science or equivalent relevant experience.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, and model optimization, training and quantization toolkits.
- 5+ years of experience in software development for complex real-time systems, imaging and CV algorithms or related signal processing fields using C / C++.
- Solid modern C / C++ programming and refactoring skills and able to understand and debug heavily threaded code.
Plusses :
- MS or PhD in EE / CS
- Experience with deep learning architectures such as CNNs, RNNs, or GANs, particularly for deployment on embedded devices.
- Theoretical knowledge in the field of machine learning, and computer vision or Audio pipeline and algorithms such as capture, render, codecs.
- Experience programming in SIMD, VLIW, and / or Vector processors and Familiarity with the custom ISA extensions
- Experience with low-level SW optimization at instruction level, loop optimization, vectorization, data organization and caching
- Prior experience with ARM or Risc-V CPUs, or Tensilica DSP architectures
- Familiarity with open source machine learning libraries and frameworks and experience with machine learning pipelines for data processing, model training, and deployment.
Day-to-Day :
- Implement, optimize and deploy machine learning models and algorithms that solve complex problems related to computer vision, speech, natural language processing, and other areas of artificial intelligence, specifically on resource-constrained devices.
- Code ML algorithms for CV and Audio application on customized processors and accelerators in C / C++ for performance, latency, and memory.
- Develop and debug software in a real-time, embedded, multiprocessor, multi-interface environment.
- Work closely with cross-functional teams, such as HW Architects, FW Engineers, Algorithm and Application Engineers across multiple disciplines (Vision, Audio) to identify opportunities for optimizing machine learning solutions
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