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

What the role needs

• Qualcomm Technologies, Inc.
• Engineering Group, Engineering Group > Machine Learning Engineering
• ## About the Role
• ## 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.

From the employer

## 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. Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). 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