Careers
Quick summary
- Work type
- On-site
- Location
- San Diego, CASanta Clara
- Posted
- 56 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 $152,075–$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 660 open roles on FindRole.
Listed pay typically runs $154,000–$231,000 across 429 roles with salary data.
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At a glance
TL;DR · Careers
Join our dynamic team as a Senior or Staff Engineer specializing in Reinforcement Learning and Behavioral Modeling for autonomous driving systems. You will design and refine advanced behavioral models using deep learning techniques such as CNNs, Transformers, and reinforcement learning methods to ensure safe and efficient vehicle operation. Your daily tasks include integrating these models with real-world data and simulation environments, developing sophisticated planning algorithms, and collaborating closely with cross-functional teams to enhance AI-driven decision-making in complex driving scenarios. Proficiency in Python, PyTorch, and experience with large-scale machine learning systems are essential, along with a track record of impactful research contributions at top-tier conferences.
Skills
What you'll do
- Design and refine behavioral models using advanced reinforcement learning techniques for safe and efficient autonomous driving.
- Integrate reinforcement learning models with real-world data and simulation frameworks to enhance model accuracy and reliability.
- Develop planning algorithms that leverage reinforcement learning to navigate complex driving scenarios safely and efficiently.
- Create and modify advanced algorithms to improve the performance of autonomous vehicle systems.
- Work on large-scale machine learning systems, including distributed training and deployment in production environments.
What we're looking for
- Ph.D. in relevant field plus 2 years of industry experience in autonomous driving or robotics.
- Expertise in reinforcement learning techniques including offline RL, reward modeling, and advanced algorithms.
- Proficiency in Python and machine learning libraries such as PyTorch for model development.
- Experience with simulation environments and real-world data for validating models and performance benchmarking.
- Strong programming skills and experience working with large-scale machine learning systems and distributed training.
- Track record of publications at top-tier AI conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL.
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