Software Engineer – AI and Deep Learning
1 month ago
Job Description:
TI is considered to be one of the technology leaders in DSPs and purpose designed accelerator for high performance, low power embedded systems. These technologies part of our processors product portfolio fuels innovative and differentiated solutions in area of Machine learning and AI. TI Processors has a strong and robust software development team who focuses on solving some of the most challenging technical problems in automotive and industrial systems. TI EdgeAI technology offers a practical embedded inference solution for next-generation vehicles, smart cameras, edge AI boxes, and autonomous machines and robots. If your passion lies in creating optimized embedded systems with software innovations in cutting edge AI technology then, TI is the right place for you
As a Software Engineer – You will find yourself in middle of solving challenging problems in embedded systems. You will be working with smart and intelligent engineers who are responsible to deliver deep learning solutions on TI processors. Your work will involve design and development of deep learning inference software targeted towards ADAS and automated driving systems, robotics and industrial analytics. Your role demands you to work across the lifecycle of a software products from requirement gathering, planning, design, coding and testing
Basic qualifications:
· Bachelor’s/Master’s degree (or equivalent experience) or PhD in Computer Science, Electronics, Electrical Engineering, Artificial Intelligence, or Applied Math
· 1-2 years of industry experience in embedded system and software in domain of machine learning
Skills needed:
· Great programmer: Programming and scripting skills in C/C++ and python, Modular and Object Oriented programming skills, familiarity with build systems – make, cmake, familiarity with Linux
· Working experience in machine learning technologies such as CNN, transformers, quantization algorithms and approaches for camera-based applications on embedded systems
· Good knowledge on machine learning frameworks (PyTorch), inference solution and exchange formats (ONNX, ONNX RunTime)
· Good knowledge of embedded systems – VLIW and SIMD processor architecture, DMA, cache
· Well verse with software development life cycle and efficient use of associated tools – Git, JIRA, bitbucket, Jenkins, containers (Dockers), CI/CD
· Strong Communication, documentation and writing skills
Primary responsibilities:
· Design and Development of deep learning inference software on TI DSPs and accelerators. Analyze performance, identify optimization areas and optimize the software to entitle the hardware capabilities
· Analyzes and writes test and procedures for the software developed
· Work with hardware architecture and design teams to feed improvement areas for next generation DSPs and accelerator for machine learning applications. Also work on pre-silicon software development environments such as simulators, Zebu
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