Multimodal AI Model Optimization Research Engineer

## **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..