XPeng Motors is one of China’s leading smart electric vehicle (EV) companies. We design, develop, and manufacture 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 behavior prediction DL engineers with strong ML/DL system design skills and software development skills. You will design and implement algorithms to predict the behavior of all traffic participants around our smart EVs. You will closely work with experts from perception, planning, and HD map teams to make our vehicles drive intelligently on all road conditions.
You will be working with a team of the best-in-class computer vision, AI systems, and software engineers to ensure the world-leading performance on our autonomous vehicles. Your work will be supported by massive data from our autonomous fleet to deliver the best autonomous driving solution.
Job Responsibilities:
- Research and develop algorithms to predict future behaviors of vehicles, cyclists and pedestrians and the evolution of the traffic scene.
- Design efficient model architectures that can run in real-time on the computing platform of our vehicles.
- Develop offline data-driven ML infrastructure for fast adaptation of the prediction ML models.
- Deliver on target behavior prediction SW and closely work with the perception and behavior planning team to achieve the most intelligent autonomous driving systems.
- Work closely with the platform and test teams for deployment and support of behavior prediction module on various car models.
- Work with massive field-testing data to continuously improve autonomous driving technologies.
Minimum Skill Requirements:
- D. or Master’s in computer science, electrical engineering, or related fields.
- Strong experience in applied deep learning including model architecture design, model training, data mining, and data analytics.
- 1+ years of leading ML/DL projects.
- 5+ years of experience in working with DL frameworks such as PyTorch, Tensorflow.
- 5+ years of R&D experience in autonomous driving, robotics or AI related fields.
- Solid understanding on data structures, algorithms, code optimization and large-scale data processing.
- Proficient in developing efficient algorithms in Python/C++.
- Excellent problem-solving skills.
Preferred Skill Requirements:
- Hands on experience in developing DL based prediction engine for autonomous driving.
- Experience in applying CNN/RNN/GNN, attention model, or time series analysis to real world problems.
- Experience in working with HDmaps.
- Experience in other ML/DL applications, e.g., reinforcement learning.
- Experience in DL model deployment and optimization tools such as ONNX and TensorRT.
What do we provide:
- A fun, supportive and engaging environment
- Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving
- Opportunity to work on cutting edge technologies with the top talent in the field
- Competitive compensation package
- Snacks, lunches and fun activities
The base salary range for this full-time position is $220,000 - $370,000, 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.