Senior or Staff Engineer - Reinforcement Learning and Planning Autonomous Driving
Listed on 2026-01-23
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Engineering
Systems Engineer, Software Engineer, Robotics
Company:
Qualcomm Technologies, Inc.
Job Area:Engineering Group, Engineering Group > ADAS R&D Systems
This position is open for Santa Clara and San Diego locations.
We are seeking an experienced Senior or Staff Engineer with expertise in Reinforcement Learning and Behavioral Modelling to advance our AI driving technology. Your work will be pivotal in creating safe, efficient, and reliable autonomous driving systems.
Minimum Qualifications:- Bachelor's degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 4+ years of Systems Engineering or related work experience.
- Master's degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 3+ years of Systems Engineering or related work experience.
- Ph.D. in Computer Science, Electrical Engineering, Mechanical Engineering, or related field and 2+ years of Systems Engineering or related work experience.
- Ph.D. + 2 years of industry experience in autonomous driving or robotics domain
- Proficient in variety of deep learning models like CNN, Transformer, RNN, LSTM, VAE, Graph
CNN etc. - Proven expertise in reinforcement learning, including areas like offline RL, reward modeling, RLHF, DPO, GPRO.
- Strong programming skills in Python and experience with machine learning libraries such as PyTorch.
- Experience working with simulation environments and real-world data for model validation and performance benchmarking.
- Experience working with, modifying, and creating advanced algorithms
- Analytical and scientific mindset, with the ability to solve complex problems.
- Excellent written and verbal communication skills, ability to work with a cross-functional team
- Track record of publications at top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL, etc.
- Familiarity with self-driving technologies, sensor data processing, and real-time decision-making algorithms.
- Experience with large-scale machine learning systems, distributed training, and deploying models in production environments.
- Design and refine behavioral models using advanced reinforcement learning techniques to ensure 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.
- Collaborate with researchers and engineers to push the boundaries of AI, driving innovation in autonomous vehicle technology.
- Works independently with minimal supervision
- Works independently with minimal supervision.
- Provides supervision/guidance to other team members.
- Decision-making is significant in nature and affects work beyond immediate work group.
- Requires verbal and written communication skills to convey information. May require basic negotiation, influence, tact, etc.
- Has a moderate amount of influence over key organizational decisions.
- Tasks do not have defined steps; planning, problem-solving, and prioritization must occur to complete the tasks effectively.
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EEO
Employer:
Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.
Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary…
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