[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All XPeng jobs](https://jobs.opennash.com/companies/xpeng/) · [Search jobs](/search/) XPeng · El Salvador # Senior Staff Machine Learning Engineer – Autonomous Driving Foundation Models El Salvador Senior individual contributor $244,140-$413,160 Data & Analytics Listed on XPeng’s official careers site. Posted March 16, 2026. Check that it is still open and apply there. [Apply on XPeng’s careers site →](https://job-boards.greenhouse.io/xpengmotors/jobs/8465375002) [OpenNash Jobs](https://jobs.opennash.com/) / [XPeng](https://jobs.opennash.com/companies/xpeng/) / Senior Staff Machine Learning Engineer – Autonomous Driving Foundation Models ## Job description XPENG 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. ### The Mission We are building the next generation of L4 autonomous vehicles. Moving beyond traditional modular stacks, we are developing large-scale Vision-Language-Action (VLA) models and World Models to handle the infinite long-tail scenarios of global driving. As a Senior Staff Machine Learning Engineer, you will architect the transition from behavior cloning to intelligent, zero-shot decision-making in diverse global markets. ### Key Responsibilities Architectural Leadership: Lead the design of end-to-end VLA architectures, bridging multi-modal perception with high-level linguistic reasoning and precise action generation. ### World Model Development Drive R&D in generative world models (latent dynamics) to create high-fidelity, controllable driving simulations for closed-loop training and evaluation. ### Policy Evolution Apply Advanced RL (Online/Offline) and IL to refine driving policies, focusing on long-horizon planning and complex multi-agent interactions. ### Scaling & Data Strategy Define scaling laws for driving foundation models, overseeing data curation, automated labeling, and post-training at a multi-billion parameter scale. ### Global Generalization Lead the model’s adaptation strategy for overseas road conditions, ensuring robust performance across varying traffic laws and driving cultures. ### Qualifications 5-8 years of expertise in Deep Learning, with a significant track record in VLM, VLA, or Embodied AI. Proven experience in training and deploying Foundation Models (Transformers, LLMs) at scale. Deep understanding of Sequential Decision Making, World Models, or Policy Gradient methods. Mastery of PyTorch and expertise in distributed training (DeepSpeed, Megatron, etc.). ### A "Product-First" mindset The ability to balance cutting-edge research with the deterministic requirements of L4 production vehicles. ### What do we provide A fun, supportive and engaging environment Infrastructures and computational resources to support your ML model development/research. Opportunity to work on cutting edge technologies with the top talent in the field. Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving Competitive compensation package Snacks, lunches, dinners, and fun activities The base salary range for this full-time position is $244,140-$413,160, 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. ## At a glance - Posted by the employer: Mar 16, 2026 - First seen by OpenNash: Oct 12, 2026 - Last checked: Oct 19, 2026 - Listed for: 217 days - Location: El Salvador - Pay: $244,140-$413,160[Apply on XPeng’s careers site →](https://job-boards.greenhouse.io/xpengmotors/jobs/8465375002) ## More jobs at XPeng ### [Senior Machine Learning Engineer - AI Foundation](https://jobs.opennash.com/companies/xpeng/jobs/e7d9b3c300fdfca9557c/) El Salvador ### [Senior Machine Learning Engineer - Foundation Model](https://jobs.opennash.com/companies/xpeng/jobs/044f0b7a4e0de026ad58/) El Salvador ### [Senior Machine Learning Engineer - LLM Quantization & Deployment](https://jobs.opennash.com/companies/xpeng/jobs/3f223699d0d5f202c9d9/) El Salvador ### [Senior Machine Learning Engineer – Predictive World Model](https://jobs.opennash.com/companies/xpeng/jobs/cd2e5b3e39b1d635c6bf/) El Salvador ### [Staff Machine Learning Engineer](https://jobs.opennash.com/companies/xpeng/jobs/b2d51dd57095ebbe13f3/) El Salvador ## Similar jobs at other companies ### [Engineer, Staff-Machine Learning-Embedded,C++](https://jobs.opennash.com/companies/qualcomm/jobs/36648b7095d4511c48c8/) Qualcomm · Hyderabad, Telangāna, India ### [Sr Staff/Principal DevOps Engineer, Machine Learning Infrastructure and Performance](https://jobs.opennash.com/companies/qualcomm/jobs/44797cbcd22659969f8e/) Qualcomm · Markham, Ontario, Canada ### [Machine Learning Engineer](https://jobs.opennash.com/companies/accenture/jobs/ef14ea91e804ba52f5de/) Accenture ### [Quantitative / Machine Learning Engineer](https://jobs.opennash.com/companies/totalenergies/jobs/259a76019d5c03765816/) TotalEnergies ### [Senior Machine Learning Engineer](https://jobs.opennash.com/companies/siemens/jobs/d151b9ceb25367914ae6/) Siemens OpenNash lists jobs from employers’ own careers sites and does not handle applications. Dates come from the employer where stated; “first seen” and “last checked” are our own observations. OpenNash Jobs · Official listings with dates and links to the employer. [Weekly hiring report](/reports/hiring/) · [Methodology](/methodology/)