Machine Learning Engineer (Speech/Audio) - Singapore

The role

You will own large-scale speech and audio data pipelines for model training. You will support model training and optimization, perform domain adaptation, and build evaluation frameworks.

What you will do

• Build and maintain large-scale speech/audio data pipelines for collection, cleaning, filtering, labeling, augmentation and quality control.
• Partner with senior speech engineers on term/hotword mining strategies.
• Contribute to fine-tuning and evaluating speech/language models.
• Improve recognition accuracy for code-switching, names, and product terms.
• Help fine-tune models using scenario-specific data for industry-specific terms.
• Build test sets and evaluation frameworks.
• Benchmark internal models against open-source and commercial baselines.

Required qualifications

• Minimum 1 year of hands-on experience in speech, machine learning, or large-scale data engineering.
• Experience in ASR/SpeechLLM model training, fine-tuning, or evaluation; LLM or general ML model training/fine-tuning; or Large-scale audio, video, or text data pipeline work.
• Solid Python and PyTorch fundamentals.
• Experience with distributed data processing (e.g., Spark, Ray).

Nice to have

• Familiarity with SpeechLLM / speech SSL concepts, or exposure to models such as StepAudio or Qwen3-Omni.
• Prior experience building or contributing to hotword/contextual-biasing or code-switching ASR improvements.
• Publications at Interspeech, ICASSP, or other top AI venues, or speech-related patents.
• Experience owning a data workstream (tens/hundreds of thousands of hours of speech) in a speech-model training project.

Benefits

• Employee Stock Ownership Plan (ESOP)
• Access to best-in-class AI tools including Gemini and Claude Code
• Choice of top-spec laptops, high-performance workstation setups, and cutting-edge Plaud devices
• Annual company offsites and team events
• Medical insurance
• WICA coverage for all full-time employees

About the company

Plaud is a Delaware-incorporated, San Francisco-based company building the real-world AI interface for professionals. It is a bootstrapped, profitable company with a $300M revenue run rate.