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Senior Machine Learning Performance Engineer
full-time•Santa Clara•$174k - $295k
About this role
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<div class="ace-line ace-line old-record-id-QEpMdg0zeoKTZsxHnvscgANXntA"><strong>XPENG</strong> is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.</div>
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<div class="ace-line ace-line old-record-id-FxGfdnue4o4QBfxSmbQc4FU6nRg">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.</div>
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<div class="ace-line ace-line old-record-id-GgnsdKVBwoahQRxOiGtcldwJn1c"><strong>Job Responsibilities:</strong></div>
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<div>Design and optimize onboard software systems to enable the deployment of large deep learning models in production vehicles, pushing the boundaries of performance, power efficiency, and latency.</div>
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<div class="ace-line ace-line old-record-id-M8RtdKAqIowFicxXxnLcwAegnIb"><strong>Minimum Skill Requirements:</strong></div>
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<div>Master or PhD in CS/CE/EE, or equivalent, with 0-3 years of industry experience. <strong>Open to recent graduates.</strong></div>
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<div>Strong expertise in C++ and Python.</div>
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<div>In-depth understanding of computer architecture and high-performance computing.</div>
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<div>Proven experience in application performance analysis and optimization.</div>
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<div class="ace-line ace-line old-record-id-XAelddKTTo0ToLx0LhUciB8Qnrd"><strong>Preferred Skill Requirements:</strong></div>
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<div>Experienced with CUDA kernels and Nvidia TensorRT</div>
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<div>Previous experience in the autonomous driving or robotics industry.</div>
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<div>Being efficiently in solving complex problems collaboratively on larger teams</div>
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<div class="ace-line ace-line old-record-id-AfuvdAZSJoQd2cxEY3mcId9enEc"><strong>What do we provide:</strong></div>
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<div>A fun, supportive and engaging environment</div>
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<div>Infrastructures and computational resources to support your work.</div>
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<div>Opportunity to work on cutting edge technologies with the top talents in the field.</div>
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<div>Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving</div>
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<div>Competitive compensation package</div>
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<div>Snacks, lunches, dinners, and fun activities</div>
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<div class="ace-line ace-line old-record-id-Phq0dnLUvopu4sxzHOjcXDK0nwd">The base salary range for this full-time position is $174,720 - $295,680, 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.</div>
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<div class="ace-line ace-line old-record-id-H3updzFZcoxPxYxLBEocCJPOn2e">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.</div>
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What you'll do
- Design and optimize onboard software systems for deploying large deep learning models in production vehicles. Focus on enhancing performance, power efficiency, and latency.
About XPENG
XPeng is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers. Its mission is to drive Smart EV transformation with technology and data, shaping the mobility experience of the future. In order to optimize its customers’ mobility experience, XPeng develops in-house its full-stack advanced driver-assistance system technology and in-car intelligent operating system, as well as core vehicle systems including powertrain and the electrical/electronic architecture. XPeng is headquartered in Guangzhou, China. In 2021, the Company established its European headquarters in Amsterdam, along with other dedicated offices in Copenhagen, Munich, Oslo, and Stockholm.The Company’s Smart EVs are mainly manufactured at its plant in Zhaoqing and Guangzhou，Guangdong province.
For more information, please visit https://heyxpeng.com.
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Frequently Asked Questions
What does XPENG pay for a Senior Machine Learning Performance Engineer?
XPENG offers a competitive compensation package for the Senior Machine Learning Performance Engineer role. The salary range is USD 175k - 296k per year. Apply through Clera to learn more about the full compensation details.
What does a Senior Machine Learning Performance Engineer do at XPENG?
As a Senior Machine Learning Performance Engineer at XPENG, you will: design and optimize onboard software systems for deploying large deep learning models in production vehicles. Focus on enhancing performance, power efficiency, and latency..
Is the Senior Machine Learning Performance Engineer position at XPENG remote?
The Senior Machine Learning Performance Engineer position at XPENG is based in Santa Clara, California, United States. Contact the company through Clera for specific work arrangement details.
How do I apply for the Senior Machine Learning Performance Engineer position at XPENG?
You can apply for the Senior Machine Learning Performance Engineer position at XPENGdirectly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process.