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Machine Learning Engineer, Ops

💼 Full-time💰 $125,000–$125,000🗓 2026-07-27 → 2026-09-25

Core

Build and scale low-latency, reliable inference infrastructure for generative audio models (TTS, voice conversion, ASR) to bridge research and production.

Role type

Senior MLOps Engineer (Inference Infrastructure)

Builds

High-performance model serving systems for streaming and batch inference

Domain

Generative AI, Audio Models, Cloud Infrastructure

Deliverable

production ML models

Required skills

Kubernetes (K8S) orchestration, CI/CD automation, Python or Go, GPU-accelerated inference, performance profiling, model architecture knowledge (TTS/ASR)

Preferred skills

Triton Inference Server, vLLM-Omni

Responsibilities

Design and maintain inference infrastructure, implement high-performance inference engines, orchestrate service deployments with autoscaling, develop CI/CD pipelines, monitor production systems for latency and resource utilization, optimize inference performance for streaming and batch applications

Seniority

Senior, hands-on IC

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