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

Build next-generation end-to-end driving intelligence with Qualcomm’s Autonomous Driving AI team. This onsite role in San Diego, CA focuses on developing deep learning systems that translate multimodal sensor inputs into safe, reliable driving behavior, supported by training infrastructure, simulation, and safety-critical evaluation.

Qualcomm offers a competitive annual discretionary bonus program, an opportunity for annual RSU grants, and a highly competitive benefits package. The annual pay range is USD 140,800 - 211,200.

What You’ll Do

• 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 incorporate vision, map, route, and vehicle context.
• Create behavioral planning and trajectory generation models.
• Work on goal-conditioned driving systems and controllable AI planning frameworks.
• Develop evaluation methodologies and metrics to measure model quality, safety, and driving performance.
• Implement simulation-based validation and closed-loop evaluation frameworks.
• Investigate failure cases and long-tail scenarios to improve robustness and generalization.
• Apply data-centric approaches such as data augmentation, synthetic data generation, curriculum learning, and self-training.
• Collaborate 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.

Requirements

• PhD in Computer Science, Engineering, Information Systems, or related field.
• Or Master’s degree in a related field with 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• Or Bachelor’s degree in a related field with 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• Master’s or Ph.D. training 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 Python, PyTorch, and C++ (preferred).
• Deep understanding of deep learning and related areas including neural network design, computer vision, Transformers, representation learning, and multimodal 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.

Technologies

• Python
• PyTorch
• C++
• ONNX
• TensorRT
• Transformers