What are the responsibilities and job description for the Machine Learning Infra Engineer position at nuancelabs?
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.
Responsibilities
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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.
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Real-Time Video Streaming: Architect systems to handle long-lived WebRTC connections with unpredictable client behavior, ensuring smooth video and audio delivery at scale.
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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.
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GPU Cluster Management: Configure and maintain GPU clusters using Kubernetes and Terraform. Implement monitoring, autoscaling based on custom metrics, and cost optimization strategies.
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Developer Tooling: Build CI/CD, evaluation, and versioning systems that enable safe, zero-downtime model deployments and rapid iteration cycles.
Requirements
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Infrastructure Expertise: Strong practical experience with Kubernetes, Terraform, and cloud platforms. You can design secure, scalable systems and debug complex distributed issues.
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Systems Programming: Proficiency in Python and experience with systems languages (Rust or Go). Comfortable profiling workloads and resolving compute, memory, or network bottlenecks.
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Orchestration & Pipelines: Experience managing large-scale offline workflows using tools like Dagster, Ray, Airflow, or similar frameworks.
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Production Operations: Deep understanding of production reliability, monitoring, incident response, and capacity planning for high-traffic services.
Preferred Experience
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Experience with WebRTC or real-time media pipelines in production
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Experience running GPU-backed inference services at scale (vLLM, Triton Inference Server, TensorRT)
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Knowledge of performance optimization and low-level systems debugging
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Familiarity with video/audio processing and storage systems
Nuance Labs Key Facts
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$10M seed round backed by Accel, South Park Commons, Lightspeed, and top angels including Synthesia’s former CPO.
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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.
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In-person collaboration, 5 days a week at Seattle HQ
Salary : $10,000,000