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About the role
- Machine Learning Engineer designing and training lightweight ASR models for mobile devices at Plaud. Contributing to optimization, multilingual data management, and deployment collaboration.
Responsibilities
- Responsible for the architectural design and training of lightweight ASR models 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.
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.
Benefits
- 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.
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