Multimodal AI Model Optimization Research Engineer

Benefits: Comprehensive medical, dental and vision coverage for employees and their families, with 100% of monthly premiums paid by Tavus Unlimited paid time off, as well as parental and pawental leave Flexible hours Remote-friendly, with teams at home or in co-working spaces across the globe Debate and feedback are cornerstones of our culture Yearly stipend for you to spend on any learning materials (i.e. newsletters, online courses, etc.) Company retreats Generous gear stipend Frequent in person meet ups Team members from diverse backgrounds – we’re looking for culture creators, not culture fits Progressive, open-minded meritocracy

Qualifications: 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 Ability to read ML papers, reproduce results, and adapt ideas Clear communication and collaboration skills 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 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 experience in deep learning using PyTorch 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