Research Engineer, Generative Video

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