Must Haves:

• Bachelor’s 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