Note: The job is a remote job and is open to candidates in USA. Tavus is a company focused on enhancing human-AI interaction through advanced multimodal AI research. The role involves optimizing cutting-edge AI models for efficiency and production readiness, collaborating with teams to implement and benchmark these systems.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- Flexible work schedules
- Unlimited PTO
- Competitive healthcare and gear stipends
- A collaborative environment focused on learning and impact
- Relocation support offered
Company Overview
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