Senior Machine Learning Engineer – End-to-End Autonomous Driving
About The Position
Qualcomm Technologies, Inc. is seeking a Senior Machine Learning Engineer to join its Autonomous Driving AI team and build end-to-end driving intelligence. The role develops deep learning systems that map multimodal sensor inputs to safe and reliable driving behavior, working across machine learning, autonomous driving, behavioral planning, large-scale training infrastructure, simulation, and safety-critical evaluation. The engineer will build and optimize production-grade autonomous driving models and machine learning workflows, including multimodal architectures, behavioral planning and trajectory generation, goal-conditioned driving systems, and evaluation and simulation frameworks. The role also contributes to robustness and generalization research, production deployment and optimization on automotive platforms, and technical innovation through algorithms, publications, and patents. The work includes end-to-end autonomous driving systems, vision-language-action models, AI driving planners, large-scale training infrastructure, closed-loop evaluation, safety-critical validation, and autonomous vehicle foundation models.
Requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field and 2+ years of hardware engineering, software engineering, systems engineering, or related work experience; or a master's degree in one of these fields and 1+ year of related work experience; or a Ph.D. in one of these fields.
- Strong programming skills in Python and PyTorch; C++ is preferred.
- Deep understanding of deep learning, machine learning, 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 machine learning workflows from data ingestion through deployment.
- Strong software engineering fundamentals, including code quality, version control, testing, and reproducible experimentation.
Nice To Haves
- 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.
- 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.
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 using 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 evaluation methodologies and metrics to measure 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 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.
Benefits
- Competitive annual discretionary bonus program.
- Opportunity for annual RSU grants, except for employees on sales-incentive plans.
- Competitive benefits package.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
