Machine Learning Engineer (Speech/Audio) - Singapore

Why You Should Join Us

• Plaud is a bootstrapped, skyrocketing, profitable company with a $300M revenue run rate achieved in just three years.
• Define the next-gen paradigm for human-AI interaction.
• Gain exposure to cutting-edge AI for Pro tools and play a direct role in our global expansion.
• Work with passionate teammates who value innovation, collaboration, and customer success.
• Grow your career in a culture that champions continuous learning and fast career development.
• Market-competitive compensation, global exposure, and a vibrant, creativity-fueled work atmosphere.

What you will do

• 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 — working alongside domain specialists on the technical algorithm design.
• 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.

Skills, qualifications and experience we look for

• Minimum 1 year of hands-on experience in speech, machine learning, or large-scale data engineering.
• Experience in AT LEAST ONE of the following:

a) ASR/SpeechLLM model training, fine-tuning, or evaluation;
b) LLM or general ML model training/fine-tuning;
c) 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) — moved up from nice-to-have, since responsibility #1 requires pipeline ownership at scale.

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.

What we offer

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

Disclaimer: Plaud is and will continue to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristics.