Associate Engineer- AI/ML-embedded, C++
Technology, Data & Digital · Software & Web Development · Software Engineering · Machine Learning · Embedded Systems
In short
Qualcomm is seeking an Associate Engineer for its Generative AI team in Hyderabad, focusing on integrating GenAI models on Qualcomm chipsets for on-device inference. This role involves developing and optimizing ML solutions like SNPE SDK, porting AI/ML models, and enhancing performance on hardware accelerators.
Responsibilities
- Development and commercialization of ML solutions like Snapdragon Neural Processing Engine (SNPE) SDK on Qualcomm SoCs.
- Developing various SW features in our ML stack.
- Porting AI/ML solutions to various platforms.
- Optimizing performance on multiple hardware accelerators (like CPU/GPU/NPU).
- Expert knowledge in deployment aspects of large software C/C++ dependency stacks using best practices.
- Keeping up with fast-paced development in industry and academia to enhance solutions from software engineering and machine learning standpoints.
Requirements
- 6+ years of relevant work experience in software development.
- Excellent analytical and debugging skills.
- Strong understanding of Processor architecture and system design fundamentals.
- Strong development & programming skills in C and C++.
- Experience with embedded systems development or equivalent.
- Excellent communication skills (verbal, presentation, written).
- Ability to collaborate across a globally diverse team and multiple interests.
- Master’s or Bachelor’s degree in Computer science or equivalent.
- 1-2 years of relevant work experience in software development.
- Basics of Deep-learning and familiarity with neural network operators.
- Good communication skills (verbal, presentation, written).
Desired Qualifications
- Experience in embedded system development.
- Experience in C, C++, OOPS and Design patterns.
- Experience in Linux kernel or driver development is a plus.
- Strong OS concepts.
- Knowledge of object-oriented software development.
- Knowledge of Processor architecture and system design fundamentals.
- Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU).
- Background in mathematical operations: linear algebra, fast-math libraries.
- Floating-point, Fixed-point representations and Quantization concepts.
- Knowledge of parallel computing systems and associated languages like OpenCL, CUDA, etc. is a plus.
#AI/ML#embedded#C++#Generative AI#Machine Learning#On-device inference#LLM#LVM#Snapdragon#SNPE SDK#SoC#NPU#Object-oriented programming#Linux kernel#Driver development