Staff ML Engineer: Edge AI Quantization Lead

Socket.dev; Santa Clara (CA); On-site; USD 161,000 - 241,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a Staff Software Engineer to join the AI Hub team and advance quantization and deployment of ML models for edge devices.

You will design and optimize quantization pipelines within AIMET, supporting PTQ, QAT, and mixed-precision techniques across edge hardware. You will implement activation and weight quantization for LLMs, develop tooling to diagnose accuracy degradation, and integrate AIMET with PyTorch and ONNX.

Qualifications

• Bachelor's degree with 4+ years of related work experience or higher degrees with fewer years.
• Master's degree with 3+ years of related work experience or higher degrees with fewer years.
• PhD with 2+ years of related work experience.

Responsibilities

• Design, develop, and maintain quantization algorithms and compression pipelines within the AIMET framework (PTQ, QAT, mixed-precision, AdaScale etc.).
• Implement advanced quantization techniques including weight-only quantization, activation quantization, KV-cache quantization, and sub-4-bit quantization for LLMs and generative AI models
• Build tooling to analyze, profile, and debug model accuracy degradation caused by quantization
• Integrate AIMET workflows with popular ML frameworks — PyTorch and ONNX
• Develop APIs and developer-facing tooling to make AIMET accessible and easy to use for external customers and design partners
• Integrate AIMET in AI Hub Workbench Quantize job to enable Quantization at large scale.
• Own end-to-end quantization and optimization of models published on Qualcomm AI Hub, ensuring they meet accuracy, latency, and power targets on Qualcomm hardware
• Quantize and validate a broad range of model families — vision transformers, LLMs, diffusion models, speech, and multimodal architectures — for deployment via AI Hub
• Develop and maintain automated quantization pipelines and evaluation harnesses to scale model onboarding across AI Hub's growing model catalog

Skills

Python

PyTorch

ONNX

TensorFlow

Quantization techniques

LLMs quantization

C++

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field

Master's degree in Computer Science, Engineering, Information Systems, or related field

PhD in Computer Science, Engineering, Information Systems, or related field

Tools

AIMET

GPTQ

AWQ

SmoothQuant

Job description

Qualcomm Technologies, Inc. is seeking a Staff Software Engineer to join the AI Hub team and advance quantization and deployment of ML models for edge devices.

You will design and optimize quantization pipelines within AIMET, supporting PTQ, QAT, and mixed-precision techniques across edge hardware. You will implement activation and weight quantization for LLMs, develop tooling to diagnose accuracy degradation, and integrate AIMET with PyTorch and ONNX.