{"id":1019204,"url":"https://alion.io/job/xpengmotors-com-ai-research-intern-predictive-world-model","title":"AI Research Intern – Predictive World Model","company":{"id":686006,"name":"XPeng","domain":"xpengmotors.com","url":"https://alion.io/company/xpengmotors","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":83,"open_postings":6,"ghost_share":0,"stale_share":0.5,"repost_share":0,"time_to_fill_p50_days":74,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States","Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":62000,"max_usd":103000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":408},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"arXiv","optional":false},{"name":"Computer Vision","optional":false},{"name":"Embodied AI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Gaussian Splatting","optional":false},{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NeRF","optional":false},{"name":"Pre-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"World Models","optional":false}],"status":"live","first_seen_at":"2026-09-18T01:11:52Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-11-05T17:23:08Z","board_verified":true,"closed_at":null,"days_open":48,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":48},"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.\nWe are seeking PhD research interns with strong expertise in generative modeling and a demonstrated record of original research. In this role, you will work alongside our research team to develop world models that learn the dynamics of the physical world from large-scale multimodal data - predicting how a scene evolves under an agent's actions, and serving as a learned simulator for training and evaluating driving and robotic policies. You will work with state-of-the-art generative architectures, including diffusion and flow-matching models, video tokenizers, and transformer-based multimodal backbones, with access to vast amounts of real-world multimodal data from our autonomous fleet and robotics platforms. Interns are expected to drive a focused research project end to end, and strong results are supported for publication at top-tier venues.\nJob Responsibilities:\nDrive a focused research project on predictive world models, spanning problem formulation, architecture design, training, evaluation, and empirical analysis, in close collaboration with a mentor and the broader research team.\n\nContribute to one or more of the following directions: high-quality multi-view future prediction and generation, supporting both action-conditioned rollouts and formulations that forecast the future without explicit action conditioning; architectures in which a shared backbone both predicts the future and produces trajectories or actions; predictive pre-training to improve Vision-Language-Action (VLA) driving performance.\n\nExtend prediction beyond 2D pixels into a shared multimodal latent space that spans 3D scene representations such as Gaussian Splatting, together with occupancy and reward signals, so that a single model can support simulation, evaluation, and policy training.\n\nInvestigate cross-embodiment generalization through unified observation and action representations and embodiment-conditioning mechanisms, so that a single world model transfers across vehicles, robots, and sensor configurations with only few-shot data.\n\nBuild evaluation methodology for predictive world models, spanning representation quality, prediction accuracy, generation fidelity, physical plausibility, long-horizon rollout consistency, and closed-loop policy performance.\n\nCollaborate with research engineers to move research prototypes into scalable training and inference pipelines, and publish and open-source results where appropriate.\n\nMinimum Skill Requirements:\nCurrently pursuing a PhD in Engineering, Computer Science, or a related field, with a focus on Deep Learning, Computer Vision, or Generative Models.\n\nFirst-author publications at top-tier venues such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, CoRL,RSS , or SIGGRAPH. Work under submission may be presented as an arXiv preprint.\n\nStrong, up-to-date foundation in generative modeling and experimental methodology, with hands-on experience building, training, fine-tuning, and evaluating models in PyTorch or JAX.\n\nStrong Python programming and software design skills, with a solid understanding of data structures, algorithms, code optimization, and large-scale data processing.\n\nAvailable to commit to a minimum of 12 weeks and work on-site at our Santa Clara office.\n\nPreferred Skill Requirements:\nHands-on experience with generative models for video or 3D, such as diffusion, flow matching, autoregressive video prediction, or neural scene representations including NeRF and Gaussian Splatting.\n\nExperience with world models or learned simulators for decision making, including model-based reinforcement learning and Vision-Language-Action (VLA) models.\n\nExperience with multimodal foundation models and video tokenizers or VAEs, including pretraining or adapting large pretrained backbones.\n\nPrior research internship experience in autonomous driving, robotics, or embodied AI, or contributions to widely used open-source projects.\n\nWhat do we provide:\nA fun, supportive and engaging environment.\n\nInfrastructures and computational resources to support your work.\n\nOpportunity to work on cutting edge technologies with the top talents in the field.\n\nOpportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.\n\nCompetitive compensation package.\n\nSnacks, lunches, dinners, and fun activities.\n\nWe 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.","description_format":"text","description_chars":5095,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Autonomous Driving","Automotive Manufacturing"],"lifecycle":[{"event":"open","at":"2026-09-18T02:29:04Z"}],"visa":[],"liveness":{"score":61,"band":"ok","label":"Likely open","p_open":1,"p_active":0.847,"p_room":0.72,"age_days":48,"expected_fill_days":74,"reasons":["conf:4","win:mid","crowd:junior"],"computed_at":"2026-11-05T05:54:30Z"},"pay":null,"html_url":"https://alion.io/job/xpengmotors-com-ai-research-intern-predictive-world-model","json_url":"https://alion.io/job/xpengmotors-com-ai-research-intern-predictive-world-model.json","meta":{"generated_at":"2026-11-05T19:46:12Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":26556,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-06T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":686006},"rest":"https://alion.io/mcp/rest/get_company?id=686006"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fxpengmotors-com-ai-research-intern-predictive-world-model"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fxpengmotors-com-ai-research-intern-predictive-world-model"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fxpengmotors-com-ai-research-intern-predictive-world-model"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/xpengmotors-com-ai-research-intern-predictive-world-model\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fxpengmotors-com-ai-research-intern-predictive-world-model"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":1019204}},{"tool":"search_jobs","arguments":{"company":"xpengmotors.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":1019204},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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