Senior AI Performance Architect
Technology, Data & Digital · Data, AI & Analytics · Machine Learning · Software Engineering · Embedded Systems
In short
Qualcomm is seeking a Senior AI Performance Architect to drive functional, performance, and power enhancements in AI accelerators for state-of-the-art training capabilities. The role involves understanding ML network trends, working with customers on hardware requirements, analyzing architectures, and designing efficient computational blocks and memory subsystems for AI models.
Responsibilities
- Understand trends in ML network design and their impact on SW and HW design.
- Work with customers to determine hardware requirements for AI training systems.
- Analyze current accelerator and GPU architectures.
- Architect enhancements for efficient AI model training.
- Design and architect flexible computational blocks supporting various datatypes and precisions.
- Design and architect memory subsystems optimized for capacity and bandwidth.
- Design and architect scale-out and scale-up architectures.
- Optimize for power efficiency.
- Perform competitive analysis.
- Codesign HW with SW/GenAI (LLM) requirements.
- Define performance models to prove architecture proposal effectiveness.
- Perform pre-silicon prediction of performance for ML training workloads.
- Analyze performance/area/power trade-offs for future HW and SW ML algorithms.
Requirements
- Master's degree in Computer Science, Engineering, Information Systems, or related field.
- 3+ years Hardware Engineering experience defining architecture of GPUs or accelerators used for training of AI models.
- In-depth knowledge of nVidia/AMD GPU capabilities and architectures.
- Knowledge of LLM architectures and their HW requirements.
Desired Qualifications
- Knowledge of computer architecture, digital circuits and hardware simulators.
- Knowledge of communication protocols used in AI systems.
- Knowledge of Network-on-Chip (NoC) designs.
- Understanding of various memory technologies used in AI systems.
- Experience in modeling hardware and workloads for performance and power estimates.
- High-level hardware modeling experience preferred.
- Knowledge of AI Training systems such as NVIDIA DGX and NVL72.
- Experience training and finetuning LLMs using distributed training frameworks like DeepSpeed, FSDP.
- Knowledge of front-end ML frameworks (i.e., TensorFlow, PyTorch).
- Strong communication skills (written and verbal).
- Detail-oriented with strong problem-solving, analytical and debugging skills.
- Demonstrated ability to learn, think and adapt in a fast-changing environment.
- Ability to code in C++ and Python.
- Knowledge of a variety of classes of ML models (i.e. CNN, RNN, etc).
Benefits
- Competitive annual discretionary bonus program.
- Opportunity for annual RSU grants.
- Highly competitive benefits package designed to support success at work, at home, and at play.
Skills
PythonC++TensorFlowPyTorchDeepSpeedFSDP
#AI#Machine Learning#Hardware#Architecture#Performance#Training#GPU#Accelerator#LLM
About Qualcomm
Enabling a world where everyone and everything can be intelligently connected.
Enabling a world where everyone and everything can be intelligently connected.\n\n
Company
QualcommJob Posted
3 days ago
Employment Type
Full Time
Work mode
On Site
Salary
US$126,700–190,100 / year
Experience Level
Senior
Locations
San Diego, United States of America
Qualification
Master
Applicants
Be an early applicant
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