Full-Time Senior Data Engineer

About UsAt 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 multi-modal AI models for human perception and understanding, combined with state-of-the-art human avatar rendering and communication models. Our models power everything from text-to-video AI avatars to real-time conversational video experiences across industries like healthcare, recruiting, sales, education, and more. 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.

The RoleData is the foundation of everything we build. We’re looking for a Senior Data Engineer who goes beyond pipelines and cleaning datasets. You’ll own our entire data strategy, from sourcing and curating to structuring and optimizing, ensuring our models and products are powered by the highest-quality data possible. You’re a true master of your craft including data sourcing, formatting, labeling, cleaning, and making use of our internal data. Your Mission Be a data visionary – You anticipate the data needs not just for today, but for the future. You know how to curate diverse, high-quality datasets to ensure AI models reach their full potential. You should have a product minded approach, and clearly understand the bigger picture of our mission and the importance of data to that. You’re constantly thinking about what data is missing for our next phase of models. Influence AI model training – Your data work will directly impact AI model performance, efficiency, and inference accuracy. You will collaborate closely with ML engineers to optimize datasets for maximum AI effectiveness. Own the data, end-to-end – from sourcing to structuring—so it’s clean, scalable, and actually useful. Be a data hunter – Web scraping, third-party deals, unconventional sources—you’ll find, collect, and curate the best multimodal data (text, video, images) to power our models. Manage large-scale data procurement to ensure our models train on the highest quality information. Master video data – AI-generated video has unique challenges, from proper classification and segmentation to structuring it for machine learning training. You will own this challenge and ensure that our video datasets are structured for AI success. Optimize labeling & automation – You will own the data labeling process and build automated workflows to make cleaning, labeling, and structuring data as efficient as possible. Work closely with our data annotation teams to ensure high-quality labeled data for ML models. Turn internal data into gold – Our own platform is a goldmine of insights—help us unlock and use it to drive smarter decisions and supercharge growth. Speed + precision – Move fast, but don’t break data. Every pipeline, dataset, and workflow should be tight, efficient, and built to last. What We’re Looking For You don’t just maintain - you build. From zero to fully running pipelines, you make things happen. You can take charge of how we use internal data to make smarter decisions. Extreme ownership - You own data strategy end-to-end, proactively solving what data we need, where to get it, and how to structure it for AI impact. Strategic mindset – You think beyond pipelines—you anticipate data needs before they arise and help shape AI development at Tavus. Previous work with LLMs, multimodal data, is a big plus. You know how to source, structure, and optimize data for real AI impact. Automation expert – You know how to automate data cleaning, structuring, and labeling workflows for efficiency and scale. ML-first mindset – You understand that better data = better models and structure datasets to maximize AI model accuracy. Fast, but flawless. Speed matters, but so does accuracy. You balance both. You don’t follow best practices—you create them. A lot of what we’re doing is new- you set the standard for how data should be done. Technical expertise – You have strong experience with Python, SQL, and large-scale data processing tools.

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