Member of Technical Staff - ML Research Engineer; Multi-Modal - Audio

At Liquid, we're redefining the architecture of intelligence itself by building efficient AI systems at every scale. We're not just building AI models—we're architecting what comes next.

Requirements

• Experience with machine learning at scale
• Worked with audio models and understand the effects of architecture choices on runtime, latency, and quality
• Proficient in PyTorch, and familiar with distributed training frameworks like DeepSpeed, FSDP, or Megatron-LM
• Worked with multimodal data (e.g. audio, text, image, video)
• Contributed to research papers, open-source projects, or production-grade multimodal model systems
• Understanding of data quality, augmentations, and preprocessing pipelines and their impact on model performance
• Experience working in interdisciplinary teams across research, systems, and infrastructure
• Designing and training multimodal language models, or specialized audio models
• Developed audio encoders or decoders, or integrated them into language pretraining pipelines
• Experience working with large-scale audio datasets and managing massive datasets effectively
• Strong programming skills in Python, with an emphasis on writing clean, maintainable, and scalable code