Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone.We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression.More about usProduct (Captions by Mirage) Research (Seeing Voices, technical-white-paper)Updates (Mirage on X / twitter)TechCrunch, Forbes AI 50, Fast Company (press)Our InvestorsWe’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.Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the RoleMirage 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.This 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.ResponsibilitiesTrain and optimize large-scale video and multimodal modelsImprove efficiency across training and inference (memory, latency, cost)Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generationBuild and maintain distributed training systemsOptimize GPU utilization, parallelism, and throughputDevelop tooling for experimentation, evaluation, and debuggingTranslate research models into robust, production-ready systemsMonitor and improve model performance in real-world usageWhat makes you a great fitBS/MS/PhD in CS, ML, or related field2+ years of professional industry experienceStrong experience in deep learning systems and infrastructureExpertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.)Experience scaling and optimizing large models under low-latency inference constraintsStrong debugging and performance profiling skillsAbility to move quickly from prototype to productionBenefits:Comprehensive medical, dental, and vision plans401K with employer matchCommuter BenefitsCatered lunch multiple days per weekDinner stipend every night if you're working late and want a bite! Grubhub subscriptionHealth & Wellness PerksMultiple team offsites per year with team events every monthGenerous PTO policyCaptions 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.Please note benefits apply to full time employees only.