3 months ago
Redmond, WA, USAMid Level
Base Salary
$150k - $160k/yr
Responsibilities
- Design, develop, and deploy Large Audio Language Models for native audio understanding, reasoning, and generation.
- Build Large Audio Reasoning Models for complex reasoning over speech and audio inputs across medical, technical, and conversational domains.
- Develop Speech-to-Speech systems covering speech understanding, dialogue management, and speech synthesis.
- Research alignment between speech encoders and LLM backbones using adapters, LoRA, and efficient fine-tuning.
- Design speech tokenization and temporal compression methods for long-form audio reasoning and multi-turn dialogue.
- Build evaluation frameworks and benchmarks for speech question answering, audio understanding, and reasoning accuracy.
- Optimize inference pipelines for low-latency and streaming speech applications.
- Transfer research innovations into production systems and customer-facing applications.
- Contribute to technical documentation, research write-ups, and publications at venues including NeurIPS, ICML, ACL, and Interspeech.
Requirements
- Master's degree in Computer Science, Electrical Engineering, or a related field with a focus on speech, audio machine learning, or multimodal learning; Ph.D. preferred.
- At least 2 years of industry or applied research experience in speech/audio AI, Large Language Models, or multimodal systems.
- Applied research contributions demonstrated through publications, patents, or shipped speech/audio AI or LLM products.
- Strong proficiency in Python and PyTorch, including hands-on GPU-accelerated training of large-scale models.
- Understanding of speech and audio signal processing, acoustic modeling, and audio representations.
- Working knowledge of Transformers, SSMs, instruction tuning, and alignment methods.
- Familiarity with adapter-based integration, cross-modal attention, and audio-text fusion.
- Preferred experience with Large Audio Language Models such as Qwen-Audio, SALMONN, LTU, or Gemini Audio.
- Preferred experience with HuBERT, Wav2Vec 2.0, Whisper, WavLM, neural audio codecs, vocoders, speech synthesis, and discrete speech tokenization.
- Preferred experience with audio reasoning benchmarks, distributed training, inference optimization, speech frameworks, multilingual speech, domain adaptation, or audio-model safety evaluation.
- Preferred publication record at top-tier venues including NeurIPS, ICML, ICLR, ACL, Interspeech, or ICASSP.
Benefits
- Competitive compensation package with comprehensive benefits.
- Opportunity to work on Large Audio Language Models and audio reasoning research with real-world impact.
- Collaboration with experienced applied scientists and engineers in speech and multimodal AI.
- Support for publications at top-tier conferences and professional development.
- Access to state-of-the-art GPU infrastructure for large-scale audio-model training.
- Flexible hybrid or remote work arrangements; locations include Redmond, Washington, and Palo Alto, California.
About Centific
Centific builds AI data and engineering platforms and services for enterprises, including curated multimodal datasets, industry‑tuned LLMs, and RAG pipelines backed by vector databases. It monetizes through software, data operations, and consulting to design, deploy, and scale GenAI systems, along with QA automation and digital engineering work. Privately held and headquartered in Redmond, Washington, the company raised a $60M Series A in 2025 to expand its AI data foundry and platform capabilities.