# Research Engineer, Generative Video

**Company:** [Mirage](https://hotfix.jobs/companies/mirage)
**Location:** New York, NY
**Role:** ML Engineering
**Salary:** $175k – $275k/yr
**Experience:** 5+ years
**Skills:** PyTorch, CUDA, Triton, Distributed Training, Fsdp, Deep Learning, Diffusion Models, Autoregressive Models, Quantization, Model Pruning, Knowledge Distillation, Gpu Optimization, Performance Profiling, Multimodal Models, Video Generation
**Posted:** 2026-08-17

> Build and scale generative video and multimodal models, optimizing training and inference for efficiency, throughput, and ultra-low latency. The role requires deep learning systems expertise, strong PyTorch/CUDA experience, and the ability to move research models into production.

## Job Description

## Responsibilities
- Train and optimize large-scale video and multimodal models.
- Improve efficiency across training and inference, including memory, latency, and cost.
- Implement distillation, quantization, and pruning techniques to 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.

## Requirements
- Bachelor’s, master’s, or PhD in computer science, machine learning, or a related field.
- 2+ years of professional industry experience.
- Strong experience with deep learning systems and infrastructure.
- Expertise in PyTorch, CUDA, Triton, and distributed training, including FSDP.
- 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.
- 401(k) with employer match.
- Commuter benefits.
- Catered lunch multiple days per week.
- Dinner stipend for late work.
- Grubhub subscription.
- Health and wellness perks.
- Multiple team offsites and regular team events.
- Generous paid time off policy.

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