Join Mirage as a Research Engineer to build and scale systems for video generation models in a collaborative AI-driven environment.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
- Train and optimize large-scale video and multimodal models
- Improve efficiency across training and inference
- Implement techniques such as distillation, quantization, and pruning
- Build and maintain distributed training systems
- Monitor and improve model performance in real-world usage
Must have
- BS/MS/PhD in CS, ML, or related field
- 2+ years of professional industry experience
- Strong experience in deep learning systems and infrastructure
- Expertise in PyTorch, CUDA, Triton, and distributed training
- Experience scaling and optimizing large models under low-latency inference constraints
Nice to have
- Strong debugging and performance profiling skills
- Ability to move quickly from prototype to production
Practical constraints
- All roles require in-person presence at NYC HQ
AI in the day-to-day
We build multimodal agents that turn creative direction into edits and integrate our models into products through APIs.
Requirements
- Experience
- 2+ years
- Education
- Bachelor's degree
Not disclosed in this posting: compensation, visa sponsorship.
Benefits
Joblaze summary
In this role, the Research Engineer focuses on enhancing the efficiency and scalability of video generation models through advanced machine learning techniques. Key skills include deep learning expertise, particularly with PyTorch and CUDA, alongside experience in optimizing large models for low-latency performance. This position is ideal for candidates with a strong technical background and at least two years of industry experience, particularly those who thrive at the intersection of research and systems engineering. The team is dedicated to pushing the boundaries of generative media, making it a compelling environment for innovation.
Joblaze insights
Quick facts
- Is the Research Engineer, Generative Video role remote?
- No — this is an on-site role in Union Square, New York City.
- How much experience is required?
- At least 2 years of relevant experience for this Research Engineer, Generative Video role.
- Where is the role based?
- Mirage is hiring for this position in Union Square, New York City.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: CUDA, PyTorch, Triton, distributed training.
- What seniority level is this role?
- Mirage targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer, Generative Video role at Mirage.
From the original posting
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.
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.
Responsibilities
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
What makes you a great fit
BS/MS/PhD in CS, ML, or related field
2+ years of professional industry experience
Strong 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
Strong debugging and performance profiling skills
Ability to move quickly from prototype to production
Benefits:
Comprehensive medical, dental, and vision plans
401K with employer match
Commuter Benefits
Catered lunch multiple days per week
Grubhub subscription
Health & Wellness Perks
Generous PTO policy
Standard company text repeated across Mirage's postings is omitted here.