ML 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

Requirements

• 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

Nice-to-Haves

• Experience with video generation models, diffusion models, or autoregressive generation

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
• Grubhub subscription
• Health & Wellness Perks
• Multiple team offsites per year with team events every month
• Generous PTO policy