Careers
Quick summary
- Work type
- On-site
- Location
- San Diego, CA
- Posted
- 53 days ago
- Nearby
- 99+ roles within 25 mi
Market check
Salary context
How this pay compares to similar roles
This listing doesn't post a salary. Most similar roles pay $152,150–$208,800.
Based on 239 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has 745 open roles on FindRole.
Listed pay typically runs $154,000–$231,000 across 423 roles with salary data.
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At a glance
TL;DR · Careers
As a Robotics AI Engineer at Qualcomm Robotics, you will join a cutting-edge team focused on developing Vision Language Action (VLA) models that enable robots to understand complex instructions and perform intricate tasks. Your daily responsibilities include researching the latest trends in robotics AI and multimodal learning, designing VLA models, building training pipelines, and optimizing these models for real-time performance on Qualcomm’s advanced platforms. You will collaborate with cross-functional teams to integrate AI capabilities into the Robotics SDK and partner solutions while contributing to internal knowledge sharing and publishing findings in top venues. The ideal candidate has a strong background in deep learning, robotics AI, Python, PyTorch or TensorFlow, and experience with model optimization for edge devices, dataset curation, and ROS 2 simulation environments.
Skills
What you'll do
- Research trends in robotics AI and multimodal learning to guide VLA model development.
- Design models integrating vision, language, and action for practical robotic applications.
- Develop and maintain training pipelines and datasets for embodied AI systems.
- Optimize and deploy AI models on Qualcomm’s platforms for real-time performance.
- Contribute to the integration of AI capabilities into Qualcomm’s Robotics SDK solutions.
What we're looking for
- Experience in designing and developing Vision-Language-Action (VLA) models for robotic applications.
- Proficiency in deep learning techniques including transformers and multimodal models.
- Strong background in robotics AI and model optimization for edge devices.
- Knowledge of dataset curation, teleoperation data, and simulation-to-real transfer.
- Familiarity with robotics systems, ROS 2, and advanced hardware platforms.
- Expertise in Python and deep learning frameworks like PyTorch or TensorFlow.
- Ability to collaborate effectively in a fast-paced, cross-functional team environment.
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