Principal Engineer/Manager

Qualcomm

Quick summary

Work type: On-site
Location: San Diego, CA
Salary: $206,900–$310,300 / yr
Posted: 45 days ago
Closes: Oct 27, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $201k

This role $259k

$131k most similar roles pay here $330k

This role pays more than 82% of similar roles. Most pay $165,000–$237,225 — the shaded band above. At the midpoint, this role pays about $259k versus about $201k for comparable roles.

Based on 238 similar postings.

Employer

About Qualcomm

Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.

Qualcomm currently has 750 open roles on FindRole.

Listed pay typically runs $154,000–$231,000 across 430 roles with salary data.

Most-posted roles

View all roles at Qualcomm

At a glance

TL;DR · Principal Engineer/Manager

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The AI Systems Team Lead at Qualcomm Technologies will oversee a team of machine learning engineers focused on designing and implementing advanced Visual Language Action Models (VLAs), Vision-Language Models (VLMs), and Large Language Models (LLMs) for low-level perception in autonomous driving and infotainment systems. The role involves optimizing accuracy-latency trade-offs, collaborating with Qualcomm’s AI teams, and engaging with automotive OEM R&D groups to deploy efficient deep learning networks on Snapdragon Ride platforms. Ideal candidates should have expertise in VLAs, VLMs, LLMs, Vision Transformers, and multi-modal fusion, along with hands-on experience in network quantization and deployment on resource-constrained devices. Strong leadership skills, technical vision, and a track record of cross-functional collaboration are essential for this role, which requires deep knowledge of machine learning fundamentals and extensive industry experience.

Skills

Python C++ TensorFlow PyTorch Kubernetes Docker CI/CD PostgreSQL Qualcomm Ride Platform Vision Transformers BEV Space Multi-modal Fusion Deep Learning Network Quantization Autonomous Driving Lidar Processing MLOps

What you'll do

Oversees team of machine learning engineers in designing state-of-the-art Visual Language Action Models.
Designs low-level perception systems for end-to-end autonomous driving on Qualcomm Ride platform.
Enhances speed and latency of deep networks operating on Snapdragon Ride AI accelerators.
Facilitates collaboration with Qualcomm horizontal AI teams and external R&D groups.
Builds a team of world-class AI/deep learning engineers, providing mentorship and guidance.

What we're looking for

PhD or equivalent experience with extensive background in machine learning.
Proven leadership in managing ML engineering teams.
Expertise in designing and implementing deep learning networks.
Experience in optimizing deep learning kernels and compilers.
Strong understanding of automotive use-case algorithms (LLP, ADAS).
Excellent communication and collaboration skills for cross-functional work.
Hands-on experience with deploying efficient networks on resource-constrained devices.

Hybrid

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