Machine Learning Engineer (Speech/Audio) - Singapore

Own large-scale speech/audio data pipelines: build and maintain systems for data collection, cleaning, filtering, labeling, augmentation and quality control to support model training. Partner with senior speech engineers on term/hotword mining strategies based on ASR system output. Support model training and optimization: contribute to fine-tuning and evaluating speech/language models (SpeechLLM or general LLM background both applicable), with focus on improving recognition accuracy for code-switching, names, and product terms. Domain adaptation: help fine-tune models using scenario-specific data to improve recognition of industry-specific terms across key languages and verticals. Evaluation: build test sets and evaluation frameworks (keyword/domain-lexicon based); benchmark internal models against open-source and commercial baselines.

Responsibilities

Own large-scale speech/audio data pipelines: build and maintain systems for data collection, cleaning, filtering, labeling, augmentation and quality control to support model training; Partner with senior speech engineers on term/hotword mining strategies based on ASR system output; Support model training and optimization: contribute to fine-tuning and evaluating speech/language models (SpeechLLM or general LLM background both applicable), with focus on improving recognition accuracy for code-switching, names, and product terms; Domain adaptation: help fine-tune models using scenario-specific data to improve recognition of industry-specific terms across key languages and verticals; Evaluation: build test sets and evaluation frameworks (keyword/domain-lexicon based); benchmark internal models against open-source and commercial baselines

Requirements

Minimum 1 year of hands-on experience in speech, machine learning, or large-scale data engineering; Experience in AT LEAST ONE of the following: ASR/SpeechLLM model training, fine-tuning, or evaluation; LLM or general ML model training/fine-tuning; Large-scale audio, video, or text data pipeline work (e.g., tens of thousands of hours of audio, or TB-scale multimodal data); 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

An Employee Stock Ownership Plan (ESOP) that gives a real stake in Plaud’s long-term success; Work in a fast-moving, product-driven environment where your ideas directly shape the future of AI productivity; Access to best-in-class AI tools, including Gemini, Claude Code, and other frontier AI systems to maximize engineering and execution efficiency; Choice of top-spec laptops, high-performance workstation setups, and cutting-edge Plaud devices for all new hires; Annual company offsites, team events, and a culture that values craftsmanship, ownership, and velocity; Comprehensive benefits to protect employees' financial security, physical health, and longterm growth; Medical insurance and WICA coverage for all full-time employees