NUANCE LABS CAREERS
ML Infra/Systems Engineer
LOCATION
Seattle, WA
EMPLOYMENT TYPE
Full time
DEPARTMENT
Engineering
About the Role
Nuance Labs is building the next generation of emotionally expressive, real-time AI.
This is a critical role to build the infrastructure that powers our AI platform. You will own the systems that serve models at scale, orchestrate complex data workflows, and ensure our real-time video AI runs reliably with low latency for users worldwide.
Key Facts
$10M seed round backed by Accel, South Park Commons, Lightspeed, and top angels including Synthesia’s former CPO.
A world-class team of PhDs from MIT, UW, and Oxford with decades of industry experience at Apple and Meta, advancing real-time avatars from cutting-edge research to products used by millions.
In-person collaboration, 5 days a week at Seattle HQ
Responsibilities
Own Inference Infrastructure: Build and maintain the serving stack for multimodal AI workloads. Optimize for latency, throughput, and cost using batching strategies, autoscaling, and intelligent resource allocation.
Real-Time Video Streaming: Architect systems to handle long-lived WebRTC connections with unpredictable client behavior, ensuring smooth video and audio delivery at scale.
Orchestrate Data Workflows: Build robust pipelines for offline processing, evaluation, and training using orchestration frameworks like Dagster or Ray. Manage petabyte-scale video storage and network requirements.
GPU Cluster Management: Configure and maintain GPU clusters using Kubernetes and Terraform. Implement monitoring, autoscaling based on custom metrics, and cost optimization strategies.
Developer Tooling: Build CI/CD, evaluation, and versioning systems that enable safe, zero-downtime model deployments and rapid iteration cycles.
Requirements
Infrastructure Expertise: Strong practical experience with Kubernetes, Terraform, and cloud platforms. You can design secure, scalable systems and debug complex distributed issues.
Systems Programming: Proficiency in Python and experience with systems languages (Rust or Go). Comfortable profiling workloads and resolving compute, memory, or network bottlenecks.
Orchestration & Pipelines: Experience managing large-scale offline workflows using tools like Dagster, Ray, Airflow, or similar frameworks.
Production Operations: Deep understanding of production reliability, monitoring, incident response, and capacity planning for high-traffic services.
Send application or questions to careers@nuancelabs.ai
