Mirage
ML Engineer, Generative Video
About this role
Mirage is hiring an ML Engineer to build and optimize large-scale video generation models, focusing on training infrastructure, inference efficiency, and bringing cutting-edge generative video systems to production. You'll work on novel modeling approaches, distributed training systems, and techniques like distillation and quantization to enable real-time, low-latency video generation.
What you'll do
- Train and optimize large-scale video and multimodal models
- Improve efficiency across training and inference (memory, latency, cost)
- Implement model acceleration techniques such as distillation, quantization, and pruning
- Build and maintain distributed training systems with optimized GPU utilization
- Develop tooling and infrastructure for experimentation, evaluation, and debugging
- Translate research models into production-ready systems and monitor real-world performance
What they're looking for
- Deep learning systems and infrastructure
- PyTorch and CUDA programming
- Triton and distributed training frameworks (FSDP)
- Model optimization under low-latency inference constraints
- Performance profiling and debugging
- Scaling large language and vision models
- Rapid prototyping to production deployment
- Video generation or diffusion/autoregressive model experience
Benefits
- Comprehensive medical, dental, and vision coverage
- 401K with employer match
- Commuter benefits and catered lunch multiple days weekly
- Dinner stipend for late work nights and Grubhub subscription
- Health & wellness perks and generous PTO policy
- Multiple team offsites and monthly team events
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Mirage
Mirage builds an AI-native video platform that leverages generative media and large language models to enable sophisticated video production, editing, and creative workflows. The company is hiring backend engineers, full-stack software engineers, ML engineers, and iOS developers to advance their AI-driven platform and enhance user experiences in web-based and mobile media creation.
View all jobs at MirageLikely interview questions
- Walk us through a project where you optimized model inference latency—what techniques did you use and what results did you achieve?
- How have you approached scaling distributed training systems, and what bottlenecks have you encountered?