Mirage
Technology
MLEngineer,GenerativeVideo
Neural analysis suggests this role is
optimal for Junior candidates.
“ML Engineer, Generative Video at Mirage. Skills: PyTorch, CUDA, Triton, FSDP, deep learning systems. Train and optimize large-scale video and multimodal models. Improve efficiency across training and inference (memory, latency, cost). Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation. Build and maintain distributed training systems. Optimize GPU utilization, parallelism, and throughput. Develop tooling for expe”
What You'll Achieve.
Bring cutting-edge models into production. Make advanced models faster, more efficient, and capable of ultra-low latency, real-time generation.
Industry & Context.
systems engineering; inference optimization; model performance
All of our roles will require you to be in-person at our NYC HQ (located in Union Square).
What They're Looking For.
Must Have
BS/MS/PhD in CS, ML, or related field. 2+ years of professional industry experience. experience in deep learning systems and infrastructure. Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.). Experience scaling and optimizing large models under low-latency inference constraints. debugging and performance profiling skills. Ability to move quickly from prototype to production.
What You'll Do.
Train and optimize large-scale video and multimodal models.
Improve efficiency across training and inference (memory, latency, cost).
Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation.
Build and maintain distributed training systems.
Optimize GPU utilization, parallelism, and throughput.
Develop tooling for experimentation, evaluation, and debugging.
Translate research models into robust, production-ready systems.
Monitor and improve model performance in real-world usage.
How You'll Work.
Team & Collaboration
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.
Full Job Description
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 us Product https://mirage.app/captions (Captions by Mirage) Research https://arxiv.org/abs/2506.08279 (Seeing Voices, technical-white-paper) Updates https://x.com/trymirage (Mirage on X / twitter) TechCrunch https://techcrunch.com/2026/03/24/mirage-raises-75m-to-continue-building-models-for-its-ai-video-editing-app-captions/, Forbes AI 50 https://www.forbes.com/companies/captions/?list=ai50, Fast Company https://www.fastcompany.com/91270234/video-most-innovative-companies-fast-company-2025-youtube-roku-tubi-vimeo-captions-descript-cour-procreate-synthesia-beeble (press) Our Investors We’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 Role 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. Th
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