{"id":1911927,"url":"https://alion.io/job/sber-senior-research-engineer-multimodal-diffusion-post-train","title":"Senior Research Engineer (Multimodal Diffusion, Post-train)","company":{"id":67,"name":"Sber","domain":"sber.ru","url":"https://alion.io/company/sber","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HeadHunter","truth_index":{"grade":"A","score":97,"open_postings":192,"ghost_share":0.063,"stale_share":0,"repost_share":0.255,"time_to_fill_p50_days":7,"computed_at":"2026-10-09T06:01:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Moscow, Russia"],"countries":["RU"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":39000,"max_usd":73000,"period":"year","method":"role_seniority_country_cell","sample_n":20},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Diffusers","optional":false},{"name":"DPO","optional":false},{"name":"FSDP","optional":false},{"name":"GRPO","optional":false},{"name":"MusicGen","optional":false},{"name":"PPO","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"SGLang","optional":false},{"name":"Stable Diffusion","optional":false},{"name":"vLLM","optional":false},{"name":"AudioCraft","optional":true}],"status":"live","first_seen_at":"2026-10-05T14:54:50Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-09T01:27:46Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Исследуем и внедряем передовые методы для инструктивного редактирования изображений/видео, интеграции аудио в видео-генерацию и повышения качества за счет RLHF (Reinforcement Learning from Human Feedback).\nОбязанности\n Разработка и обучение диффузионных моделей для инструктивного редактирования видео и изображений.\n Исследование архитектур для совместной генерации видео и синхронизированного аудио по текстовому промпту.\n Создание пайплайна RLHF для тонкой настройки моделей:\n Обучение мультимодальных reward-моделей (видео/аудио/текст).\n Интеграция алгоритмов RL (PPO, DPO, GRPO, OPD) в диффузионный пайплайн.\n Проектирование экспериментов, анализ результатов.\n Тесная коллаборация с Distributed Engineers для эффективной имплементации идей.\n Требования\n Сильный бэкграунд в CV, генеративных моделях (Diffusion, GANs), мультимодальном ML.\n Опыт работы с диффузионными моделями (Stable Diffusion/FLUX, Wan 2.X и пр.) и фреймворками (Diffusers).\n Практические знания Reinforcement Learning, особенно RLHF.\n Уверенное владение PyTorch и навыки распределенного обучения (DDP/FSDP).\n Способность быстро прототипировать и проводить исследования SOTA методов.\n Опыт работы с SGLang, vLLM, Transformers\n Бонус: Опыт с аудио-генерацией (AudioLDM, MusicGen), публикации на NeurIPS/ICML/CVPR.\n Условия\n комфортный современный офис рядом с м. 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