Senior Machine Learning Engineer - End-to-End Autonomous Driving

Company:

Qualcomm Technologies, Inc.

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

General Summary:

About the Role

We are seeking a highly motivated Senior Machine Learning Engineer to join our Autonomous Driving AI team and help build the next generation of end-to-end driving intelligence. In this role, you will develop advanced deep learning systems that directly map multimodal sensor inputs into safe and reliable driving behavior.

You will work at the intersection of machine learning, autonomous driving, behavioral planning, large-scale training infrastructure, simulation, and safety-critical evaluation. The ideal candidate is passionate about building production-grade AI systems and advancing the state of the art in autonomous vehicle technology.

Responsibilities

• 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 that leverage vision, map, route, and vehicle context information.
• Design and implement behavioral planning and trajectory generation models.
• Develop goal-conditioned driving systems and controllable AI planning frameworks.
• Create robust evaluation methodologies and metrics for measuring model quality, safety, and driving performance.
• Develop simulation-based validation and closed-loop evaluation frameworks.
• Investigate failure cases and long-tail scenarios to improve model robustness and generalization.
• Design data augmentation, synthetic data generation, curriculum learning, and self-training approaches.
• Collaborate closely with perception, planning, simulation, systems, and software engineering teams.
• Drive innovation through new algorithms, technical leadership, publications, and patent generation.
• Contribute to production deployment and optimization of machine learning models on automotive platforms.

Minimum Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.

Preferred Qualifications:

• Master's or Ph.D. in Computer Science, Electrical Engineering, Robotics, Machine Learning, Artificial Intelligence, or a related field.
• 5+ years of industry or research experience in machine learning, deep learning, computer vision, robotics, or autonomous driving.
• Strong programming skills in: PythonPyTorchC++ (preferred)
• Deep understanding of: Deep LearningMachine LearningNeural Network DesignComputer VisionTransformersRepresentation LearningMultimodal Learning
• Experience training and evaluating large-scale deep learning models.
• Experience building end-to-end ML workflows from data ingestion through deployment.
• Strong software engineering fundamentals including code quality, version control, testing, and reproducible experimentation.
• Experience in autonomous driving, ADAS, robotics, or embodied AI.
• Experience with end-to-end planners and AI planning systems.
• Experience with trajectory prediction, motion planning, or behavior modeling.
• Experience with reinforcement learning, imitation learning, or self-supervised learning.
• Experience building simulation and closed-loop evaluation frameworks.
• Familiarity with ONNX, TensorRT, distributed training, and model optimization techniques.
• Publications at top-tier conferences such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or CoRL.
• Experience filing patents or developing novel machine learning technologies.

What You'll Work On

• End-to-End Autonomous Driving Systems
• Vision-Language-Action (VLA) Models
• AI-Based Driving Planners
• Goal-Conditioned Driving Policies
• Large-Scale Deep Learning Training Infrastructure
• Trajectory Prediction and Vehicle Behavior Modeling
• Closed-Loop Evaluation and Simulation
• Safety-Critical Validation Pipelines
• Data-Centric AI and Long-Tail Learning
• Autonomous Vehicle Foundation Models

Why Join Us

You will have the opportunity to solve some of the most challenging problems in artificial intelligence and autonomous driving while working with a world-class team of researchers and engineers. Your work will directly influence the development of next-generation autonomous vehicle technologies deployed at scale.

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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 information, to the extent those requirements are permissible under applicable law.

Pay range and Other Compensation & Benefits:

$140,800.00 - $211,200.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer – and you can review more details about our US benefits at this link.

If you would like more information about this role, please contact Qualcomm Careers.