General Summary:
As part of Qualcomm AI Systems Solution CoE (Center of Excellence) team, you will develop leading-edge products and solutions around best-in-class Qualcomm high-performance inference accelerators for cloud, edge and hybrid AI applications. In this role, you will be developing and delivering System solution software for requirements across automotive, cloud and industrial IoT BUs, and drive overall system solutions. This covers a broad range of technical tasks, starting from industry leading and customer specific use cases, a spectrum of technologies to define AI/ML system solutions, ML models optimization (including GenAI/ LLMs/ LVMs/ LMMs) and ensure efficient and scalable deployment on inference accelerators and edge devices of different formfactors (phone, IHH, AI PC, AI Appliance).
Qualcomm AI Systems engineers collaborate across functional teams to meet and exceed system-level requirements and standards. This is your opportunity to work on the leading-edge AI technologies and systems, current product and future roadmap designed for AI inference acceleration and to addresses unique requirements in energy efficient AI compute.
If you think you have what it takes to be part of team that develops world class ML systems software and your skill set matches with the below job description, we will be happy to discuss with you further.
Required Skills and Aptitudes
Hands-on experience in ML/AI tools development involving Deep Learning frameworks like Pytorch 1.x, 2.x, TensorFlow, ONNX, etc…
Strong understanding of model architectures across CV, NLP, LLMs, LVMs and Multi-Modal NWs
Strong understanding and experience in working on inference graph optimization, Quantization, pruning and compression techniques etc.
Understanding of performance and accuracy metrics for different class of neural NWs
Detailed understanding of AI edge and server systems, infrastructure and industry standards
Hands-on Experience with Object Orientated Design, design patterns
Strong python / C++ implementation skills (Skill level > 7/10)
Strong in Data structures & Algorithms (Skill level > 7/10)
Hands on knowledge of LLM fine tuning, Quantization aware training is a plus
Knowledge of machine learning runtimes like ONNX Runtime, Pytorch and TF runtimes is a plus
Experience in survey of competitor toolchain and survey latest trends in the industry and academia
Develop new and innovative ideas (e.g. IDFs) for a product or feature area.
Excellent analytical, development, and debugging skills
Desirable Skills and Aptitudes
Experience with GPUs, machine learning accelerators and related software is a plus
Knowledge of ML compilers like TVM, GLOW, XLA is a plus
Hands on use of version control tools like GIT, GITHUB
Qualifications
Bachelor's / Masters/ PHD degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field.
1 – 13 years Software Engineering or related work experience.
Minimum Qualifications:
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