GPU Machine Learning Engineer
Description For GPU Machine Learning Engineer
Qualcomm Innovation Center, Inc. is seeking a talented GPU Machine Learning Engineer to join their GPU Software team. This role presents an exciting opportunity to work at the intersection of graphics and machine learning, developing cutting-edge solutions for next-generation devices.
The position involves working with Qualcomm's Snapdragon chipsets, where you'll be responsible for developing and optimizing software for the latest Machine Learning models. You'll be working on the Graphics software stack and Machine Learning SDKs across multiple platforms including Android, Linux, and Windows.
As a GPU Machine Learning Engineer, you'll be at the forefront of implementing and optimizing Adreno GPU drivers for standard APIs such as OpenCL, OpenGL ES, Vulkan, and DirectX. Your work will directly impact the performance and capabilities of machine learning applications on Qualcomm's devices.
Key responsibilities include:
- Accelerating Machine Learning operations for both inference and training on GPUs
- Implementing cutting-edge Machine Learning models, including Large Language Models (LLMs) and Large Vision Models (LVMs)
- Developing interfaces to Machine Learning frameworks
- Creating comprehensive documentation and sample code
- Collaborating with hardware designers to optimize hardware/software interfaces
- Working closely with partners, external developers, and OEMs
The ideal candidate will have a strong foundation in C/C++ programming, deep understanding of Machine Learning theory, and familiarity with frameworks like PyTorch. Experience with GPGPU APIs such as CUDA or OpenCL is essential.
Qualcomm offers a competitive compensation package including:
- Base salary range of $98,900 - $148,300
- Annual discretionary bonus program
- RSU grants
- Comprehensive healthcare benefits
- 401k plan
- Professional development opportunities
Join Qualcomm's GPU Software team to work on groundbreaking technology that powers the next generation of mobile and embedded devices. You'll be part of a collaborative environment where you can grow your skills while working on challenging and impactful projects.
Responsibilities For GPU Machine Learning Engineer
- Developing software for Machine Learning models on next generation devices
- Working on Graphics software stack and Machine Learning SDKs on Android, Linux and Windows
- Developing & optimizing Adreno GPU drivers for standard APIs
- Implementing interfaces to Machine Learning frameworks
- Acceleration of Machine Learning operations for inference and training on GPU
- Implementation of latest Machine Learning models including LLMs and LVMs
- Writing samples and documentation
- Development of unit tests
Requirements For GPU Machine Learning Engineer
- Bachelor's degree in Applied Mathematics, Computer Science, Computer Engineering, Electrical Engineering, Software Engineering, or related field
- Strong C/C++ programming skills
- Strong knowledge of Machine Learning Theory
- Familiarity with Deep Learning Framework such as Pytorch
- Familiarity with GPGPU API such as CUDA or OpenCL
- Understanding of data structures and algorithms
- Excellent interpersonal and analytical skills
Benefits For GPU Machine Learning Engineer
- Competitive annual discretionary bonus program
- Annual RSU grants
- Medical Insurance
- Dental Insurance
- Vision Insurance
- 401k
