Ai Research Engineer • Mid-Level

Who you are

You have experience with machine learning at scale and have worked with audio models, understanding the effects of architecture choices on runtime, latency, and quality. Proficiency in PyTorch is essential, and familiarity with distributed training frameworks like DeepSpeed, FSDP, or Megatron-LM is highly valued. You have experience working with multimodal data, including audio, text, image, and video, and have contributed to research papers, open-source projects, or production-grade multimodal model systems. You understand how data quality, augmentations, and preprocessing pipelines can significantly impact model performance, and you have built tooling to support that. You enjoy working in interdisciplinary teams across research, systems, and infrastructure, and can translate ideas into high-impact solutions.

What you'll do

At Liquid AI, you will be part of a team redefining the architecture of intelligence. Your role will involve shaping model architectures and scaling development platforms to enable enterprise deployments. You will work on efficient general-purpose AI systems that operate on-device and at the edge, under real-time constraints. Your contributions will directly influence the development of AI systems that can run on CPUs with low latency and minimal memory. You will collaborate with world-class engineers and researchers, contributing to the next generation of AI technologies that are already being implemented in various industries, including consumer electronics, automotive, life sciences, and financial services.

What we offer

Liquid AI offers a dynamic work environment where innovation thrives. You will have the opportunity to work on groundbreaking AI technologies that have the potential to transform industries. We believe in fostering a community of talented individuals who are passionate about pushing the boundaries of what is possible with AI. Our team is committed to creating an inclusive and collaborative culture where every member can contribute to our mission of building efficient AI systems at every scale. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds.