About the roleWe are looking for a Research Engineer to join the research team at ElevenLabs, focused on deploying and optimizing our frontier AI models in production. The quality of our models only matters if they can be served fast, reliably, and at scale. You will own the systems that turn research breakthroughs into real-time products used by millions. You will thrive in this role if you enjoy:
- Deploying state-of-the-art models to production and owning the path from research checkpoint to serving infrastructure.
- Optimizing inference performance across the stack, including latency, throughput, and cost, using techniques such as quantization, distillation, KV-cache optimization, batching strategies, and custom kernels.
- Building and tuning high-performance serving systems for real-time, streaming workloads where every millisecond matters.
- Creating tooling and infrastructure that lets researchers ship new models to production quickly, safely, and with confidence in their performance characteristics.
RequirementsWe do not require any formal certifications or degrees. Instead, we are seeking enthusiastic engineers who can showcase solving impressively hard problems with artifacts such as past projects, designs, or GitHub contributions. Ideally, you bring:
- Experience deploying and serving ML models in production, ideally for latency-sensitive or real-time applications.
- Strong engineering skills in GPU programming and inference optimization (e.g., CUDA, Triton, TensorRT, or serving frameworks such as vLLM or SGLang).
- The capacity to autonomously profile, diagnose, and eliminate bottlenecks across the serving stack, from model architecture to kernels to orchestration, and to build the tooling to measure it.
LocationThis role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.
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