Senior Machine Learning Engineer - Perception Foundation

XPeng Motors is one of China’s leading smart electric vehicle (“EV”) companies. We design, develop, manufacture and market smart EVs that are seamlessly integrated with advanced Internet, AI and autonomous driving technologies. We are committed to in-house R&D and intelligent manufacturing to create a better mobility experience for our customers. We strive to transform smart electric vehicles with technology and data, shaping the mobility experience of the future.   We are looking for a full-time Machine Learning Engineer - Perception Foundation, with deep knowledge and strong enthusiasm towards establishing a state-of-art Perception foundation for training/evaluting large perception models and accelerating model training/inference.   Our mission is to solve the autonomous driving problem. You will work with a team of talented software engineers, machine learning engineers and research scientists to push the boundary of state-of-art machine learning models which will enable the next-generation E2E solution of autonomous driving.   Job Responsibilities:

• Design, train, and deploy large perception models that can leverage the vast amount of labeled and unlabeled data from a fleet of million vehicles.You will be working with a team of best-in-class computer vision/deep learning engineers to ensure best perception performance on our autonomous vehicles. Your work will ensure that we deliver the most reliable mass market autonomous vehicle solution.

  Job Responsibilities:

• Research, prototype, optimize and deploy state-of-the-art perception (3D/2D detection, segmentation and classification, etc.) algorithms for production autonomous vehicles which includes developing deep learning and/or traditional computer vision algorithms.
• Train large-scale deep learning models on GPU clusters and improve algorithms through tracked evaluation metrics.
• Optimize utilization of deep learning compute resources via quantization, pruning and other novel techniques
• Work closely with software and test teams on development of algorithms/modules on simulation and on-target platforms

  Minimum Skill Requirements:

• Ph.D. degree or equivalent in Computer Science, Electrical / Mechanical Engineering, Physics, Applied Mathematics, Statistics or related field
• 3 years + of experience in deep learning algorithms or autonomous driving industry.
• Strong hands-on skills with at least one of the following deep learning frameworks (PyTorch, TensorFlow, etc.)
• Familiar with classical computer vision algorithms such as multiview geometry
• Proficient in developing algorithms in either C/C++ or Python
• Strong will to research, develop and apply deep learning algorithms to new problems
• Good communication skills to convey information and results clearly

  Preferred Skill Requirements:

• Research experience in Deep Learning or Computer Vision
• Strong publication in top AI conferences (CVPR, ICCV, ECCV, NIPS, ICML, ICLR, etc.) or experience in Kaggle competition
• Experience with classical Lidar point cloud algorithms such as plane fitting and clustering

  What do we provide:

• A fun, supportive and engaging environment
• Opportunities to pursue and work on cutting edge technologies
• Competitive salary
• Snacks, lunches, dinners and fun activities

  The base salary range for this full-time position is $150,000 - $250,000, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.   We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.