Machine Learning Engineer (On-device ASR) - San Francisco

Machine Learning Engineer (On-device ASR) - San Francisco About Plaud Inc. Plaud is building the world's most trusted AI work companion for professionals to elevate productivity and performance through note-taking solutions, loved by over 1,500,000 users worldwide since 2023. With a mission to amplify human intelligence, Plaud is building the next-generation intelligence infrastructure and interfaces to capture, extract, and utilize what you say, hear, see, and think. Plaud Inc. is a Delaware-incorporated, San Francisco-based company pushing the boundary of human–AI intelligence through a hardware–software combination. With SOC 2, HIPAA, GDPR, ISO27001, ISO27701, and EN18031 compliance, Plaud is committed to the highest standards of data security and privacy protection. To learn more about Plaud, please visit http://www.plaud.ai/https://www.Plaud.ai and follow along on Instagram https://www.instagram.com/plaud_official/, https://twitter.com/PLAUDAI%22HYPERLINK%20%22https:/twitter.com/PLAUDAI%22%20%5C%22HYPERLINK%20%22https:/twitter.com/PLAUDAI%22%20%5CX https://twitter.com/PLAUDAI, Facebook https://www.facebook.com/plaudai, LinkedIn https://www.linkedin.com/company/plaudai/?viewAsMember=true, and YouTube https://www.youtube.com/@PLAUDAI Why You Should Join Us Plaud is building the next generation intelligence infrastructure and interfaces to capture, extract, and utilize intelligence from what people say, hear, see, and think. - Plaud is a bootstrapped, skyrocketing, profitable company with a $250M 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 - On-Device Model Design & Training: Responsible for the architectural design and training of lightweight ASR models (e.g., Streaming Transducer, CTC) for mobile and embedded devices, minimizing parameter count and computational overhead while maintaining high recognition accuracy. - Model Compression & Optimization: Lead the end-to-end optimization of ASR models using quantization, pruning, and knowledge distillation to meet stringent power, memory, and latency requirements on edge devices. - Multilingual Data Engineering: Manage the cleaning, alignment, and augmentation of multilingual speech data; address cold-start challenges for low-resource languages and enhance model robustness in complex, noisy environments. - Inference & Deployment Collaboration: Partner with engineering teams on model conversion. Minimum Qualifications - Experience Requirements: Master’s or PhD in Computer Science, Signal Processing, or a related field, with 3–5 years of experience in speech algorithms. Must have a proven track record of deploying on-device or offline ASR models. - Framework Proficiency: Expert-level command of PyTorch or TensorFlow, with deep proficiency in at least one mainstream E2E ASR framework (e.g., Wenet, Espnet, Icefall/K2, Zipformer) and a thorough understanding of their underlying architectures. - Optimization Expertise: Demonstrated hands-on experience in model compression and Post-Training Quantization (PTQ) workflows, with the ability to independently resolve quantization-induced accuracy degradation. Preferred Qualifications - Extreme Optimization Experience: Proven success in deploying voice interaction features on highly resource-constrained chips or hardware environments. - Edge-Native Architectures: Deeply familiar with SOTA architectures optimized for on-device performance (e.g., Zipformer, Paraformer, SenseVoice) or hands-on experience in Knowledge Distillation from Large Speech Models (SpeechLLMs ... (truncated, view full listing at source)