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Research Engineer, Generative Video

Mirage
New York City, USA
Full-time
Entry · 2+ years experience
Onsite
USD 175000-275000 yearly / year
Discovered 1 weeks ago
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More about us

Product (Captions by Mirage)

Research (Our Models and Agents)

Updates (Mirage on X / twitter)

TechCrunch , Forbes AI 50 , Fast Company (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.

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
  • Dinner stipend every night if you're working late and want a bite!
  • Grubhub subscription
  • Health & Wellness Perks
  • Multiple team offsites per year with team events every month
  • Generous PTO policy
  • Captions 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.

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