P

Plaud.ai

AI-powered hardware for transcription and summaries

Machine Learning Engineer - Inference & Serving, Speech LLM

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Hands-on experience building and deploying high-throughput, ultra-low-latency inference engines for large language models or foundational speech models.
  • Understanding of tradeoffs between latency, throughput, and Time-To-First-Token or Time-To-First-Audio in real-time streaming environments.
  • Practical experience with continuous batching, KV cache management such as PagedAttention, and stateful connections for real-time conversational AI.
  • Deep understanding of GPU architectures, including NVIDIA Ampere and Hopper, and memory hierarchies to identify and eliminate hardware bottlenecks.
  • Ability to communicate and collaborate across machine learning training and backend infrastructure teams.
  • Ability to work in fast-moving environments and optimize performance across GPU clusters.
  • Interest in building AI systems that understand and generate speech.

Desired Qualifications

  • Experience with modern LLM serving frameworks such as vLLM, TensorRT-LLM, SGLang, or NVIDIA Triton Inference Server; open-source contributions to these repositories are a plus.
  • Experience handling continuous audio streams over WebSockets or WebRTC, deploying neural audio codecs, and managing chunked audio generation to minimize conversational latency.
  • Experience implementing advanced generation algorithms such as speculative decoding, lookahead decoding, or chunked prefill.
  • Experience with post-training quantization and deploying models in FP8, INT8, AWQ, or GPTQ without degrading audio naturalness or ASR accuracy.
  • Experience deploying multi-GPU tensor-parallel and multi-node inference pipelines, and managing autoscaling infrastructure using Kubernetes.

About the Company

Plaud.ai

AI-powered hardware for transcription and summaries

Plaud AI makes AI-powered hardware and software that capture, transcribe, and summarize audio. Its PLAUD NOTE and NotePin record conversations and feed the data to the Plaud Intelligence platform, which uses models from OpenAI, Anthropic, and Google to produce transcripts, summaries, mind maps, and actionable items. It combines device sales with a subscription for enhanced features and expanded enterprise offerings, including PLAUD for Business after acquiring StarJar in 2025. The goal is to turn conversations into structured notes and insights to boost productivity for professionals and students.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2021

Recently Posted Jobs

Explore more opportunities at Plaud.ai

See more jobs