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

Plaud•San Francisco, CA

21h•$150,000 - $240,000•Hybrid

About The Position

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. 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. Joining Plaud offers the opportunity to define the next-gen paradigm for human-AI interaction, gain exposure to cutting-edge AI for Pro tools, and play a direct role in global expansion. The company fosters a culture that values innovation, collaboration, customer success, continuous learning, and fast career development, offering market-competitive compensation, global exposure, and a vibrant, creativity-fueled work atmosphere.

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.
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.
Demonstrated hands-on experience in model compression and Post-Training Quantization (PTQ) workflows, with the ability to independently resolve quantization-induced accuracy degradation.

Nice To Haves

Proven success in deploying voice interaction features on highly resource-constrained chips or hardware environments.
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) to compact models.
A record of published research on model lightweighting or on-device ASR in top-tier conferences like ICASSP or Interspeech, or a significant contributor to high-star open-source optimization projects on GitHub.

Responsibilities

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.
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.
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.
Partner with engineering teams on model conversion.

Benefits

Opportunity to join the founding team of this new initiative, with meaningful ownership and impact on a fast-growing startup.
Competitive Compensation: $150K-$240K base salary+performance bonus+Equity.
Top-tier healthcare for employees and dependents, including dental and vision, and a generous employer subsidy.
401(k) plan for full time employees with company matching.
Unlimited PTO, plus 13 paid holidays.
12 weeks of paid time off to spend time with your new family, regardless of gender.
Minimum of 3x in office per week.
New hires are equipped with their choice of new top-of-the-line laptops and workstation setups.
Best office equipment.
Annual offsites.
Free office drinks and snacks.