<div><div><div><div><span><span><strong>XPENG</strong> is a leading smart technology company at the forefront of innovation, integrating advanced </span><span>AI</span><span> and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (</span><span>eVTOL</span><span>) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&amp;D in AI, </span><span>machine learning</span><span>, and smart connectivity.</span></span></div><div><div><div> </div><div>We are looking for a full-time Staff Machine Learning Engineer - Inference, with deep knowledge of ML inference and strong enthusiasm towards<strong> optimize our models to utilize every FLOP and every byte of </strong><strong>RAM</strong><strong> of our </strong><strong>AI</strong><strong> accelerator hardware. </strong></div><div> </div><div>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 solution of autonomous driving.</div><div> </div><div> </div><div><strong>Job Responsibilities:</strong></div><ul><li><div>Optimization of models towards deployment on customized AI accelerators</div></li><li><div>Write kernels for customized AI accelerators</div></li><li><div>Develop performance estimates for critical kernels</div></li></ul><div> </div><div><strong>Minimum Skill Requirements:</strong></div><ul><li><div>Master in CS/CE/EE, or equivalent, in industry experience</div></li><li><div>Strong code skill in C/C++ and Python</div></li><li><div>Experience with CUDA programming or related AI accelerator programming.</div></li><li><div>Experience with enabling accuracy machine learning modeling inference using low precision data formats</div></li><li><div>Familiarity with the fundamentals of deep learning</div></li><li><div>Have strong engineering skills to unblock yourself and are willing to pick up whatever knowledge you are missing to get the job done</div></li></ul><div> </div><div><strong>Preferred Skill Requirements:</strong></div><ul><li><div>Have an understanding of ML architecture and an intuition for how to reduce model latency</div></li><li><div>Familiarity with GPU architecture or custom silicon chip architecture</div></li><li><div>Experience training deep learning models</div></li><li><div>A track record of efficiently solving complex problems collaboratively on larger teams of ML engineers, compiler engineers, kernel writers etc.</div></li></ul><div> </div><div><strong>What do we provide:</strong></div><ul><li><div>A fun, supportive and engaging environment</div></li><li><div>Infrastructures and computational resources to support your work.</div></li><li><div>Opportunity to work on cutting edge technologies with the top talents in the field.</div></li><li><div>Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving</div></li><li><div>Competitive compensation package</div></li></ul><div> </div><div>The base salary range for this full-time position is $179,400 - $303,600, 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><div> </div><div>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></div></div></div></div></div>

<p>XPENG is a leading tech company that designs, develops, manufactures, and markets intelligent mobility solutions. We explore the diversity of mobility including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. We focus on creating a future of mobility that uses thoughtful and empathetic intelligence to improve the driving experience. XPENG is committed to in-house R&amp;D, with almost 40% of our employees working in R&amp;D-related areas helping to develop our expanding product portfolio. The Company has created a full-stack Advanced Driver Assistance System (XPILOT), as well as an intelligent operating system (Xmart OS) for an enhanced in-car experience. XPENG has also developed core vehicle systems for enhanced driving capabilities, including powertrains and advanced electronic architecture. XPENG is headquartered in Guangzhou, China with multi-regional offices in Beijing, Shanghai, Shenzhen, Silicon Valley, and San Diego. In 2021, the Company established its European headquarters in Amsterdam, along with other dedicated offices in Copenhagen, Munich, Oslo, and Stockholm. XPENG's EVs are manufactured at the fully-owned plant located in Zhaoqing, China. To further expand our production capacity, two new self-owned intelligent EV manufacturing bases in Guangzhou and Wuhan are under construction now.</p>

Staff Machine Learning Engineer - Inference

<div><div><div><div><span><span><strong>XPENG</strong> is a leading smart technology company at the forefront of innovation, integrating advanced </span><span>AI</span><span> and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (</span><span>eVTOL</span><span>) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&amp;D in AI, </span><span>machine learning</span><span>, and smart connectivity.</span></span></div><div><div><div>&nbsp;</div><div>We are looking for a full-time Staff Machine Learning Engineer - Inference, with deep knowledge of ML inference and strong enthusiasm towards<strong> optimize our models to utilize every FLOP and every byte of </strong><strong>RAM</strong><strong> of our </strong><strong>AI</strong><strong> accelerator hardware. </strong></div><div>&nbsp;</div><div>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 solution of autonomous driving.</div><div>&nbsp;</div><div>&nbsp;</div><div><strong>Job Responsibilities:</strong></div><ul><li><div>Optimization of models towards deployment on customized AI accelerators</div></li><li><div>Write kernels for customized AI accelerators</div></li><li><div>Develop performance estimates for critical kernels</div></li></ul><div>&nbsp;</div><div><strong>Minimum Skill Requirements:</strong></div><ul><li><div>Master in CS/CE/EE, or equivalent, in industry experience</div></li><li><div>Strong code skill in C/C++ and Python</div></li><li><div>Experience with CUDA programming or related AI accelerator programming.</div></li><li><div>Experience with enabling accuracy machine learning modeling inference using low precision data formats</div></li><li><div>Familiarity with the fundamentals of deep learning</div></li><li><div>Have strong engineering skills to unblock yourself and are willing to pick up whatever knowledge you are missing to get the job done</div></li></ul><div>&nbsp;</div><div><strong>Preferred Skill Requirements:</strong></div><ul><li><div>Have an understanding of ML architecture and an intuition for how to reduce model latency</div></li><li><div>Familiarity with GPU architecture or custom silicon chip architecture</div></li><li><div>Experience training deep learning models</div></li><li><div>A track record of efficiently solving complex problems collaboratively on larger teams of ML engineers, compiler engineers, kernel writers etc.</div></li></ul><div>&nbsp;</div><div><strong>What do we provide:</strong></div><ul><li><div>A fun, supportive and engaging environment</div></li><li><div>Infrastructures and computational resources to support your work.</div></li><li><div>Opportunity to work on cutting edge technologies with the top talents in the field.</div></li><li><div>Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving</div></li><li><div>Competitive compensation package</div></li></ul><div>&nbsp;</div><div>The base salary range for this full-time position is $179,400 - $303,600, 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><div>&nbsp;</div><div>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></div></div></div></div></div>

Staff Machine Learning Engineer - Inference

About the Job

About the Company

Xpeng Motors

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