Member of Technical Staff - Multi-Modal - Audio

About the Company

Spun out of MIT CSAIL, Liquid AI builds general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability.

Responsibilities

• Build and scale data pipelines for audio model training, including preprocessing, augmentation, and quality filtering at scale
• Design, implement, and maintain evaluation systems that measure multimodal performance across internal and public benchmarks
• Fine-tune and adapt audio models for customer-specific use cases, owning delivery from requirements through deployment
• Contribute production code to the core audio repository, collaborating with infrastructure and research teams
• Support experimentation under real hardware constraints

Requirements

• Strong programming fundamentals with ability to write clean, maintainable, production-grade code
• Experience building and shipping production ML systems (data pipelines, evals, serving infrastructure)
• Proficiency in PyTorch
• Familiarity with distributed training frameworks like DeepSpeed or FSDP
• Track record of collaborating effectively in shared codebases with high engineering standards

Preferred Qualifications

• Direct experience with audio/speech models (ASR, TTS, vocoders, diarization, or speech-to-speech systems)
• Experience designing and running large-scale training experiments on distributed GPU clusters
• Open-source contributions demonstrating code quality and engineering judgment

Benefits

• Competitive base salary with equity
• 100% medical, dental, and vision premiums for employees and dependents
• 401(k) matching up to 4% of base pay
• Unlimited PTO plus company-wide Refill Days