{"id":1648026,"url":"https://alion.io/job/institute-of-foundation-models-machine-learning-engineer-world-modeling","title":"Machine Learning Engineer – World Modeling","company":{"id":99421,"name":"Institute of Foundation Models","domain":"ifm.ai","url":"https://alion.io/company/institute-of-foundation-models","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":95,"open_postings":42,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":482,"computed_at":"2026-11-05T05:54:30Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Abu Dhabi, United Arab Emirates"],"countries":["AE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"PyTorch","optional":false},{"name":"Unreal Engine","optional":false},{"name":"World Models","optional":false},{"name":"C++","optional":true},{"name":"Diffusion Models","optional":true},{"name":"Knowledge Distillation","optional":true},{"name":"Model Distillation","optional":true}],"status":"live","first_seen_at":"2025-07-10T05:59:05Z","employer_posted_date":"2025-07-10","last_verified_at":"2026-11-05T17:13:01Z","board_verified":true,"closed_at":null,"days_open":483,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":482},"description":"About the Institute of Foundation Models\nThe Institute of Foundation Models (IFM) at MBZUAI is a research lab dedicated to meaningful foundation model research - building models from scratch, understanding them deeply, and publishing work that shapes the field. You’ll work alongside world-class researchers and engineers on problems that directly define the models we ship.\nThe Role\nJoin the PAN world model project - our effort to build world models: foundation models that simulate, predict, and interact with the physical world. As a Machine Learning Engineer, you’ll own the engineering backbone of PAN: large-scale video and simulation data pipelines, distributed training for diffusion transformers, game-engine simulation environments, and world-model integration into robotics - turning research ideas into reliable, scalable systems.\nWhat You'll Do\nBuild and maintain large-scale video and simulation data pipelines - collection, cleaning, annotation, and filtering - to support world model training.\nDevelop and optimize distributed training systems for large-scale diffusion transformers and world models.\nBuild interactive simulation environments (e.g., Unreal Engine, Blueprint-based gyms, game integrations) for training and evaluating world models.\nIntegrate world action models / video action models into robotics systems.\nOptimize inference and serving for real-time interaction, and turn research prototypes into reliable, reproducible systems.\nWhat We're Looking For\nBSc or above in Machine Learning, Computer Science, Robotics, or a related field, or equivalent industry experience.\nHands-on experience with state-of-the-art video generative models and world models (e.g., Cosmos-3, LTX 2.3, Self-Forcing, Lingbot-World, or comparable systems).\nDeep expertise in at least one of the following areas:\nFull-stack data pipelines - large-scale video data pipelines and/or simulation data collection; annotation and filtering workflows for video / world model training.\nModel training & infrastructure - training large-scale diffusion transformers on large GPU clusters.\nRendering engines & simulation - Unreal Engine and Blueprint-based gym environments, game-engine integration, building interactive simulated environments.\n World action models & robotics - world action models / video action models, action-conditioned video generation, world-model applications in robotics.\n\nStrong engineering expertise in deep learning frameworks such as PyTorch, with the ability to debug failures across the training/inference stack (memory issues, deadlocks, I/O bottlenecks).\nHighly proficient with modern AI coding agents and web-based coding tools (e.g., Claude Code, Codex, Cursor), and skilled at leveraging them to dramatically accelerate engineering workflows.\nNice to Have\nExperience accelerating diffusion model inference (distillation, few-step generation, real-time interactive generation).\nPractical experience with web scraping and crawling frameworks (e.g., scrapy, playwright, selenium) for web-scale data curation.\nExperience with Unreal Engine C++/Blueprint development or other game-engine programming.\nExperience deploying world models in robotics or embodied-AI 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