Dice
Computer Vision Engineer V
Dice, Sunnyvale, California, United States, 94087
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Intelliswift Software Inc, is seeking the following. Apply via Dice today!
Must Have skills:C++, Python required
Background in Electrical engineering/computer science, past experience in CPU- DSP architectures, ARM, Silica, x86, low-level software optimization.
Machine learning, Pytorch similar machine learning frameworkResponsibilities: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 applications 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.
Minimum Qualifications: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.
Preferred Qualifications: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 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.
Computer Vision Engineer V#J-18808-Ljbffr
Must Have skills:C++, Python required
Background in Electrical engineering/computer science, past experience in CPU- DSP architectures, ARM, Silica, x86, low-level software optimization.
Machine learning, Pytorch similar machine learning frameworkResponsibilities: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 applications 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.
Minimum Qualifications: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.
Preferred Qualifications: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 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.
Computer Vision Engineer V#J-18808-Ljbffr