Company:
Qualcomm India Private Limited
Job Area:
Engineering Group, Engineering Group > Systems Engineering
General Summary:
Job Overview:
The Qualcomm Cloud Computing team is developing hardware and software for Machine Learning solutions spanning the data center, edge, infrastructure, automotive market. We are seeking ambitious, bright, and innovative engineers with experience in machine learning framework development. Job activities span the whole product life cycle from early design to commercial deployment. The environment is fast-paced and requires cross-functional interaction daily so good communication, planning and execution skills are a must.
Key Responsibilities
Improve and optimize key Deep Learning models on Qualcomm AI 100.
Build deep learning framework extensions for Qualcomm AI 100 in upstream open-source repositories.
Collaborate and interact with internal teams to analyze and optimize training and inference for deep learning.
Build software tools and ecosystem around AI SW Stack.
Work on Triton, ExecuTorch, Inductor, TorchDynamo to build abstraction layers for inference accelerator.
Optimize workloads for both scale-up (multi-SoC) and scale-out (multi-card) systems.
Optimize the entire deep learning pipeline including graph compiler integration.
Apply knowledge of software engineering best practices.
Desirable Skills and Aptitudes
Deep Learning experience or knowledge – LLMs, Natural Language Processing, Vision, Audio, Recommendation systems.
Knowledge of the structure and function of different components of Pytorch, TensorFlow software stacks.
Excellent C/C++/Python programming and software design skills, including debugging, performance analysis, and test design.
Ability to work independently, define requirements and scope, and lead your own development effort.
Well versed with open-source development practices.
Strong developer with a research mindset – strives to innovate.
Avid problem solver – should be able to find solutions to key engineering and domain problems.
Knowledge of tiling and scheduling a Machine learning operator is a plus.
Experience in using C++ 14 (advanced features)
Experience of profiling software and optimization techniques
Hands on experience writing SIMD and/or multi-threaded high-performance code is a plus.
Experience of ML compiler, Auto-code generation (using MLIR) is a plus.
Experiences to run workloads on large scale heterogeneous clusters is a plus.
Hands-on experience with CUDA, CUDNN is a plus.
Qualifications:
Bachelor's / Masters/ PHD degree in Engineering, Machine learning/ AI, Information Systems, Computer Science, or related field.
2+ years Software Engineering or related work experience.
2+ years’ experience with Programming Language such as C++, Python.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
OR
Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.
Applicants: If you need an accommodation, during the application/hiring process, you may request an accommodation by sending email toaccommodationsupport
Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm’s toll-free number found herefor assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.
Qualcomm is an equal opportunity employer and supports workforce diversity.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.
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