below marketmost similar roles pay hereabove market
This role pays less than
84%
of similar roles. Most pay
$200,787–$254,750
— the blue band above.
At the midpoint, this role pays about
$176k
versus about
$228k
for comparable roles.
Based on 240 similar postings.
Employer
About Qualcomm
Qualcomm is a leading American semiconductor and telecommunications company based in San Diego, CA.
Qualcomm currently has
580 open roles
on FindRole.
Listed pay typically runs
$147,900–$218,400
across 557 roles with salary data.
The Senior Machine Learning Engineer joins the Autonomous Driving AI team to build next-generation end-to-end driving intelligence. This role involves developing advanced deep learning systems that map multimodal sensor inputs into safe driving behaviors. Key responsibilities include designing scalable machine learning pipelines for data processing, training, and deployment, as well as developing multimodal architectures leveraging vision, map, and route information. You will build behavioral planning models, trajectory generation systems, and goal-conditioned driving policies. The role requires proficiency in Python, PyTorch, and C++, with expertise in Transformers, representation learning, and computer vision. You will solve complex problems in autonomous vehicle foundation models, trajectory prediction, and safety-critical validation using simulation-based frameworks, distributed training, and model optimization techniques like ONNX and TensorRT to improve robustness in long-tail scenarios.
What does a Machine Learning Engineer earn in California?
Median $236000 from 195 postings across 33 companies.
Design, develop, and optimize state-of-the-art end-to-end autonomous driving models.
Build scalable machine learning pipelines for data processing, training, validation, and deployment.
Develop multimodal deep learning architectures using vision, map, route, and vehicle context.
Design and implement behavioral planning and trajectory generation models.
Create robust evaluation methodologies and metrics for measuring model safety and performance.
Develop simulation-based validation and closed-loop evaluation frameworks.
Design data augmentation, synthetic data generation, and curriculum learning approaches.
Contribute to the production deployment and optimization of models on automotive platforms.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant work experience.
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of relevant work experience.
PhD in Computer Science, Engineering, Information Systems, or related field.
Master's or Ph.D. in Computer Science, Electrical Engineering, Robotics, Machine Learning, Artificial Intelligence, or a related field (preferred).
5+ years of industry or research experience in machine learning, deep learning, computer vision, robotics, or autonomous driving (preferred).
Strong programming skills in Python, PyTorch, and C++ (preferred).
Deep understanding of Deep Learning, Machine Learning, Neural Network Design, Computer Vision, Transformers, Representation Learning, and Multimodal Learning.
Experience in autonomous driving, ADAS, robotics, or embodied AI (preferred).