{"id":95278,"url":"https://alion.io/job/mirage-research-engineer-generative-video-2","title":"Research Engineer, Generative Video","company":{"id":6327,"name":"Mirage","domain":"mirage.app","url":"https://alion.io/company/mirage","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":175000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"FSDP","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"Model Distillation","optional":false},{"name":"Multimodal AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"Triton","optional":false}],"status":"live","first_seen_at":"2026-08-17T00:55:56Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-16T03:40:03Z","board_verified":true,"closed_at":null,"days_open":60,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":60},"description":"Mirage is an AI video company focused on making creation dramatically easier. Our team tackles some of the hardest creative and technical challenges in generative media.\nWe get to rethink how people collaborate with AI that can actually do creative work with them-defining entirely new interaction paradigms for AI-native video tools. We make that possible by building multimodal agents that turn creative direction into edits, rendering engines that composite multiple layers of video and graphics, and generative video models trained from the ground up that create new media when needed.\nAll of this comes together in Captions, our creative workspace for generating, editing, and designing video. The technology behind Captions is now available more broadly: Tesseract gives any AI agent native video-editing capabilities, while developers can integrate our models into their own products through APIs.\nExplore our work\nCaptions - Our flagship creative workspace \nTesseract - Our professional video engine for AI agents \nResearch - The foundation models we build in-house \nUpdates - The latest from Mirage \nTechCrunch, Forbes, Fast Company - Press\nOur Investors\nWe’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more.\nPlease note that most of our roles will require you to be in-person at our NYC HQ (located in Union Square) \nAbout the Role\n Mirage is seeking an ML Engineer to build and scale the systems powering our video generation models. You’ll work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production.\nThis role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation.\nResponsibilities\nTrain and optimize large-scale video and multimodal models\n\nImprove efficiency across training and inference (memory, latency, cost)\n\nImplement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation\n\nBuild and maintain distributed training systems\n\nOptimize GPU utilization, parallelism, and throughput\n\nDevelop tooling for experimentation, evaluation, and debugging\n\nTranslate research models into robust, production-ready systems\n\nMonitor and improve model performance in real-world usage\n\nWhat makes you a great fit\nBS/MS/PhD in CS, ML, or related field\n\n2+ years of professional industry experience\n\nStrong experience in deep learning systems and infrastructure\n\nExpertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.)\n\nExperience scaling and optimizing large models under low-latency inference constraints\n\nStrong debugging and performance profiling skills\n\nAbility to move quickly from prototype to production\n\nBenefits:\nComprehensive medical, dental, and vision plans\n\n401K with employer match\n\nCommuter Benefits\n\nCatered lunch multiple days per week\n\nDinner stipend every night if you're working late and want a bite!\n\nGrubhub subscription\n\nHealth & Wellness Perks\n\nMultiple team offsites per year with team events every month\n\nGenerous PTO policy\n\nCaptions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.\nPlease note benefits apply to full time employees only.","description_format":"text","description_chars":3919,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Generative Video","Multimodal AI","Generative Audio & Music"],"lifecycle":[{"event":"open","at":"2026-08-17T00:55:56Z"}],"visa":[],"liveness":{"score":18,"band":"cold","label":"Long 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