Member of Technical Staff, GPU Optimization

Captions is the leading AI video company—our mission is to empower anyone, anywhere to tell their stories through video. Over 10 million creators and businesses have used Captions to simplify video creation with truly novel and groundbreaking AI capabilities.

We are a rapidly growing team of ambitious, experienced, and devoted engineers, researchers, designers, marketers, and operators based in NYC. As an early member of our team, you’ll have an opportunity to have an outsized impact on our products and our company's culture.

Our Technology

Mirage Announcement our proprietary omni-modal foundation model

Seeing Voices (technical paper) generating A-roll video from audio with Mirage

Mirage Studio for generating expressive videos at scale

"Captions: For Talking Videos” available in the iOS app store

Press Coverage

Lenny’s Podcast: Interview with Gaurav Misra (CEO)

Latest Fundraise: Series C Announcement

The Information: 50 Most Promising Startups

Fast Company: Next Big Things in Tech

Business Insider: 34 most promising AI startups

TIME: The Best Inventions of 2024

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, 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)

We do not work with third-party recruiting agencies, please do not contact us**

About the Role

As an expert in making AI models run fast—really fast—you live at the intersection of CUDA, PyTorch, and generative models, and get excited by the idea of squeezing every last bit of performance out of modern GPUs. You will have the opportunity to turn our cutting-edge video generation research into scalable, production-grade systems. From designing custom CUDA or Triton kernels to profiling distributed inference pipelines, you'll work across the full stack to make sure our models train and serve at peak performance.

Key Responsibilities

• Optimize model training and inference pipelines, including data loading, preprocessing, checkpointing, and deployment, for throughput, latency, and memory efficiency on NVIDIA GPUs

• Design, implement, and benchmark custom CUDA and Triton kernels for performance-critical operations

• Integrate low-level optimizations into PyTorch-based codebases, including custom ops, low-precision formats, and TorchInductor passes

• Profile and debug the entire stack—from kernel launches to multi-GPU I/O paths—using Nsight, nvprof, PyTorch Profiler, and custom tools

• Work closely with researchers to co-design model architectures that are hardware-friendly and maintain state-of-the-art quality

• Stay on the cutting edge of GPU and compiler tech (e.g., Hopper features, CUDA Graphs, Triton, FlashAttention, and more) and evaluate their impact

• Collaborate with infrastructure and backend teams to improve cluster orchestration, scaling strategies, and observability for large experiments

• Provide clear, data-driven insights and trade-offs between performance, quality, and cost

• Contribute to a culture of fast iteration, thoughtful profiling, and perfo