Actively hiring· Posted 51 minutes ago

Multimodal AI Model Optimization Research Engineer

Full TimeRemote
Salary
Not disclosed
Experience
Any
Work mode
Remote

The role

About the role

2 min read

## **About Us**

At Tavus, we're building the human layer of AI. Our mission is to make human-AI interaction as natural as face-to-face interaction, enabling the human touch where it has been previously unscalable.

We achieve this through pioneering research in multimodal AI for modeling human-to-human communication (language, audio, and video), as well as generating audio-visual avatar behavior. Our models power everything from text-to-video AI avatars to real-time conversational video experiences across industries like healthcare, recruiting, sales, and education.

By enabling AI to see, hear, and communicate with human-like authenticity, we're creating the foundation for the next generation of AI employees, assistants, and companions.

We are a Series B company backed by top investors, including Sequoia, Y Combinator, and Scale VC. Join us in driving the future of human-AI interaction.

## **The Role**

We’re looking for an experienced Research Scientist/Engineer with a focus on model optimization to join our core AI team.

Our ideal partner-in-crime thrives in startup environments, is comfortable prioritizing independently, and is willing to take calculated risks. We’re moving fast and looking for people who can help pave the path.

## **Your Mission**

  • Take cutting-edge research models and make them fast, efficient, and production-ready using sparsification, distillation, and quantization
  • Own the optimization lifecycle for key models: define metrics, run experiments, and benchmark trade-offs across latency, cost, and quality
  • Partner closely with researchers and engineers to turn new ideas into deployable systems

## **Requirements**

  • Strong experience in deep learning using PyTorch
  • Hands-on experience with model optimization and compression, including knowledge distillation, pruning/sparsification, quantization, and mixed precision
  • Understanding of efficient architectures such as low-rank adapters
  • Strong understanding of inference performance and GPU/accelerator fundamentals
  • Strong Python coding skills and reliable research engineering practices
  • Experience working with large models and datasets in cloud environments
  • Ability to read ML papers, reproduce results, and adapt ideas
  • Clear communication and collaboration skills

## **Preferred Experience**

  • Optimization of diffusion models, video/audio generative models, or large language models
  • Experience with real-time or streaming systems (low-latency APIs, WebRTC, streaming TTS/video)
  • Familiarity with TensorRT, ONNX Runtime, TVM, Triton, or XLA
  • Experience writing custom Triton/CUDA kernels or low-level performance tuning
  • Experience with experiment tracking, benchmarking, and profiling at scale
  • Prior experience in research engineering or applied science roles

## **Location**

This position is preferably hybrid in San Francisco, with relocation support offered. Remote candidates are also considered.

## **Benefits**

When you join Tavus, you’re joining a family. We offer flexible work schedules, unlimited PTO, competitive healthcare and gear stipends, and a collaborative environment focused on learning and impact.

## **Culture & Diversity**

We are not looking for cultural fits — we are looking for culture creators. Diversity drives our success, and we combine varied backgrounds, skills, and perspectives to build the best experiences for our clients..

Tavus