Cantina Labs is a social AI company, developing a suite of advanced real-time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you're excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
We are looking for an ML Engineer to own the production inference stack for our text-to-speech (TTS) and speech recognition (ASR) models, end to end. Our research team delivers trained model checkpoints; you will productionize them as low-latency, real-time streaming services that run cost-efficiently on GPUs. The role covers the inference engines, the Kubernetes infrastructure they run on, and the performance benchmarking and accuracy validation that let us ship changes safely. You will bridge research and production, and own latency, throughput, cost and accuracy as we scale.
What You’ll Do:Build and optimize streaming inference engines for TTS and ASR models, including multi-stage model pipelines.
Optimize latency (time to first chunk, p50/p99) and throughput using continuous batching, CUDA Graphs, torch.compile and mixed precision.
Maintain numerical parity with the reference implementation through automated accuracy regression tests, per stage and end to end.
Deploy and operate GPU inference services on Kubernetes: autoscaling, containerization and infrastructure as code.
Build CI/CD for model artifacts, with model versioning and reproducible releases.
Own observability and performance benchmarking: p50/p99 latency, real-time factor (RTF), GPU utilization and cost per request.
Partner with research to productionize new models.
Hands-on experience deploying, scaling and optimizing ML models in production, beyond consuming model APIs.
Working knowledge of the full inference stack, from CUDA kernels to serving frameworks, with depth in some layers; expertise across all of them is not expected.
GPU performance optimization: profiling (Nsight Systems, PyTorch Profiler), memory bandwidth, CPU-GPU synchronization.
Solid understanding of model serving: continuous batching, KV cache management, request scheduling.
Production experience with Kubernetes, CI/CD and cloud infrastructure.
Strong Python and PyTorch, and a rigorous approach to performance benchmarking.
Experience with speech or audio models (TTS, ASR, voice conversion).
Experience with inference frameworks such as vLLM (vLLM-Omni), SGLang, TensorRT-LLM, TensorRT or Triton Inference Server.
When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in-office employees
One Medical membership, and more!
Skills Required
- Deep understanding of modern audio model architectures (TTS, ASR) and their inference requirements.
- Hands-on experience with Kubernetes (K8S), container orchestration, and implementing autoscaling strategies for production.
- Background in MLOps, including CI/CD automation and managing scalable cloud infrastructure.
- Proficiency in software engineering principles and experience with Python or Go for infrastructure tooling and backend services.
- Experience with GPU-accelerated inference and performance profiling techniques.
- Experience implementing and managing high-performance inference engines.
- Familiarity with high-performance inference engines (e.g., Triton Inference Server, vLLM-Omni).
- Experience optimizing inference performance for both streaming and batch applications.
What We Do
Cantina Labs, founded by Sean Parker, is a new social platform with the most advanced AI character creator. Build, share, and interact with AI bots and your friends directly in the Cantina or across the internet. Cantina bots are lifelike, social creatures, capable of interacting wherever humans go on the internet. Recreate yourself using powerful AI, imagine someone new, or choose from thousands of existing characters. Bots are a new media type that offer a way for creators to share infinitely scalable and personalized content experiences combined with seamless group chat across voice, video, and text.
