Conversational Modelling Research Engineer
About Us
is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms.
Imagine a friend who can discuss any topic with you. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale.
We’re a Series B company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners.
Be part of shaping a future where humans and machines truly understand each other.
The Role
We’re looking for an AI Researcher to join our core AI team and push the boundaries of Foundation Multimodal Conversational Models. If you thrive in fast-moving startup environments, enjoy experimenting with new ideas, and love seeing your work come to life in production then you’ll feel right at home.
Your Mission 🚀
Conduct research on Large Multimodal Models in the context of Conversational Avatars (e.g. Neural Avatars, Talking-Heads).
Develop methods to model both verbal and non-verbal aspects of conversation, adapting and controlling avatar behavior in real time, with low-latency.
Experiment with fine-tuning, adaptation, and conditioning techniques to make AudioVisual Multimodal Models, more expressive, controllable, and task-specific.
Partner with the Applied ML team to take research from prototype to production.
Stay up to date with cutting-edge advancements — and help define what comes next.
You’ll Be Great At This If You Have:
A PhD (or near completion) in a relevant field, or equivalent research experience.
Hands-on experience with Large Multimodal Models and a strong foundation in generative (language) models. This could be in the context of tasks such as VQA, Audio/Video understanding tasks, captioning behavioral analysis, Translation tasks, Speech to Speech systems.
Experience in fine-tuning/adapting VLMs for control, conditioning, or downstream tasks.
Solid background in deep learning and foundation modes.
Strong PyTorch skills and comfort building deep learning pipelines.
Nice-to-Haves
Knowledge of large-scale model training and optimization.
Experience in duplex-conversational model.
Broader understanding of generative AI across modalities.
Exposure to software development best practices.
A flexible, experimental mindset i.e. comfortable working across research and engineering.
(Bonus) Publications at EMNLP, COLING, NeurIPS, ICLR, CVPR, ICCV.
Location
Preferred: San Francisco (hybrid) or London.
Remote within the U.S. or Europe available for exceptional candidates.
Software Engineer, Infrastructure
About Us
Tavus is a research lab pioneering human computing. We’re building AI Humans: a new interface that closes the gap between people and machines, free from the friction of today’s systems. Our real-time human simulation models let machines see, hear, respond, and even look real—enabling meaningful, face-to-face conversations. AI Humans combine the emotional intelligence of humans with the reach and reliability of machines, making them capable, trusted agents available 24/7, in every language, on our terms.
Imagine a therapist anyone can afford. A personal trainer that adapts to your schedule. A fleet of medical assistants that can give every patient the attention they need. With Tavus, individuals, enterprises, and developers can all build AI Humans to connect, understand, and act with empathy at scale.
We’re a Series B company backed by world-class investors including Sequoia Capital, Y Combinator, and Scale Venture Partners.
Be part of shaping a future where humans and machines truly understand each other.
The Role
We're hiring a Senior Software Engineer (Infrastructure) to own the systems behind CVI, our real-time conversational product. Every live conversation between a person and a PAL runs on infrastructure your team owns. You'll take goals like uptime, latency, and cost and chase them wherever they lead, including into backend services and product code.
What you'll own
CVI's inference deployments. The GPU infrastructure serving live conversations across multiple providers and regions. You'll join as an early senior member of a growing infra team, working on projects like tuning the newest GPU generations and cutting cold-start and model load times so users wait less.
Expanding our GPU footprint. You'll bring on new providers and regions, stand up clusters on EKS, and build the routing, scheduling, and throughput needed for fast weight loading.
Uptime. You'll be one of the people pushing our uptime bar higher, along with the security and SOC2 work that keeps our infrastructure trustworthy.
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Fix what you find. When you see a problem, you have the trust and the mandate to fix it or flag it. Reworking our deploy pipeline so shipping is fast and boring is exactly the kind of thing you'd take on.
What this role has shipped
Multi-provider, multi-region inference infrastructure: routes live conversations across GPU providers and regions, so one provider's outage never becomes a user's problem
CUDA optimizations for Phoenix, our video rendering model: doubled the frame rate by tracing and optimizing hot paths with our researchers
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Parallel conversations on a single GPU: several live conversations sharing one card, multiplying what the fleet can serve
Who you are
You own outcomes. You don't stop where "infrastructure" ends. If the fix lives in backend code or the CVI stack, you dive in, and you don't wait for a ticket to do it.
You're energized by unfamiliar problems. If the next thing that matters is standing up a training deployment you've never touched, you jump in and learn on the fly.
You adapt as priorities evolve. In a space moving this fast, the most important thing to build can change as we learn. When it does, you adjust course without losing momentum.
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You care about this problem. Keeping large-scale, real-time systems fast and reliable is something you think about unprompted.
Requirements
Hands-on GPU inference experience. You've deployed and optimized inference workloads on GPUs and know what it takes to build reliable systems on top of GPU cloud providers.
Kubernetes and EKS depth, including routing and scheduling. You're comfortable designing how work gets placed across a fleet, and writing the services that make it happen.
Deep AWS experience. You're at home spinning up new services and turning them into simple, repeatable processes others can build on.
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A senior track record of ownership. You've set technical direction, made decisions others built on, and carried ambiguous work over the finish line. You explain complex ideas clearly, to engineers and non-engineers alike.
Nice to have
Experience with GCP
Experience with video streaming infrastructure
Experience with training infrastructure or LLM serving
Experience with SOC2 or security compliance
If you don't check every box but this sounds like the work you want to be doing, apply anyway.
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
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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
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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
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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..
Data Engineer /ML Ops
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 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.
We're a Series A company backed by top investors, including Sequoia, Y Combinator, and Scale VC.
Join us in driving the future of human-AI interaction.
The Role
Data 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.
Your Mission
• Be a data visionary, anticipating future data needs
• Influence AI model training through high-quality data
• Own data end-to-end: sourcing, structuring, scaling
• Source and curate multimodal data (text, video, images)
• Master video data challenges for ML training
• Optimize labeling and automation workflows
• Unlock value from internal platform data
• Balance speed with precision
What We’re Looking For
• Extreme ownership of data strategy
• Strategic, ML-first mindset
• Experience with LLMs and multimodal datasets
• Strong automation skills
• Strong Python, SQL, and large-scale data processing experience
• Ability to define best practices in new problem spaces
Benefits
Flexible work schedule, unlimited PTO, competitive healthcare and gear stipends, and a collaborative team culture. Tavus is a place to learn, drive impact, and grow alongside a team you love.
We are not looking for cultural fits — we are looking for culture creators. Diversity is at the core of how we hire, communicate, and work.
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