This role pays less than
91%
of similar roles. Most pay
$202,800–$254,750
— the shaded band above.
At the midpoint, this role pays about
$174k
versus about
$229k
for comparable roles.
Based on 240 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has
623 open roles
on FindRole.
Listed pay typically runs
$148,300–$222,500
across 603 roles with salary data.
As an AI Researcher, On-Device LLM Efficiency within the Machine Learning Research team, you will conduct fundamental research to develop innovative machine learning methodologies that achieve beyond state-of-the-art performance. Your daily responsibilities involve researching and developing LLM inference efficiency algorithms, designing efficient model architectures, and conducting LLM training while addressing practical challenges specific to on-device constraints. You will implement and evaluate these solutions in both simulation and on-device environments. The role requires expertise in deep learning, Transformers, and Python and PyTorch programming. Key technical focus areas include LLM reasoning, inference acceleration, efficient attention, and KV cache compression. This position addresses the critical challenge of optimizing large language model performance for deployment across mobile, edge, auto, and IOT products to enable next-generation experiences on localized hardware.
Generative AI
LLM
LVM
Multi-modal
VLA
Python
PyTorch
Quantization
Model Compression
Deep Learning
Machine Learning
Systems Engineering
Hardware Engineering
LLM
PyTorch
Python
Triton-Inference Server
vLLM
SGLang
CUDA
Triton
torch.compile
torchDynamo
Distributed Systems
Kernel Design
Deep Learning
KV-Cache Management
Model Optimization