AI Researcher (Voice)
TavusFull Time
Senior (5 to 8 years)
Candidates must have a minimum of 8 years of industry experience or 5+ years of research/postdoc experience in building and deploying generative AI systems. Proficiency in PyTorch, JAX, or other deep learning frameworks is essential. Expertise in one or more generative AI areas such as LLMs, coding agents, diffusion models, autoregressive models, VAE/GAN architectures, retrieval-augmented generation, neural rendering, or multi-agent systems is required. Familiarity with transformer architectures and attention mechanisms is necessary, along with hands-on experience in large-scale training (e.g., ZeRO, DDP, FSDP, TP, CP) and data processing (e.g., Ray, Spark). Production-quality software engineering skills in Python are highly relevant. An MS or PhD or equivalent experience in Computer Science, Machine Learning, Applied Math, Physics, or a related field, and 12+ years of relevant software development experience are needed. Familiarity with high-performance computing, GPU acceleration, influential open-source libraries or publications, multimodal data, and NVIDIA GPU-based compute clusters or simulation environments are preferred.
The Senior Generative AI Research Engineer will design, post-train, and optimize foundation models for real-world applications. They will contribute to collaborative development of large-scale training infrastructure, high-efficiency inference pipelines, and scalable data pipelines. Responsibilities include working with research, software, and product teams to deploy world models from idea to production, collaborating on open-source and internal projects, authoring technical papers or patents, and mentoring junior engineers. The role involves rapid prototyping and iteration on experiments across cutting-edge AI domains such as agentic systems, reinforcement learning, reasoning, and video generation. Additionally, they will design and implement model distillation algorithms for size reduction and diffusion step optimization, and profile and benchmark training and inference pipelines to meet production-ready performance requirements.
Designs GPUs and AI computing solutions
NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.