Senior Research Engineer, JAX

Maintain and evolve the JAX training framework for scalability and efficiency in large-scale distributed training runs.Optimize production JAX inference systems for speech-to-text models using advanced techniques like continuous batching, model sharding, paged attention, and quantization.Refactor and modernize model architectures and infrastructure, translating research prototypes into production-ready systems.Investigate and resolve performance bottlenecks across the stack, from low-level kernels (XLA, Pallas) to high-level system design.Design and deploy scalable, distributed workloads optimized for TPU and GPU architectures.Bridge Research and Engineering teams to ensure seamless knowledge transfer and alignment on technical priorities.ExperienceExpert-level proficiency with JAX and its ecosystem (Flax, Optax, XLA compilation pipeline).Strong experience optimizing inference systems for production, ideally with LLMs or speech models.Hands-on experience with TPU programming and optimization; GPU/CUDA expertise is also valuable.Passion for refactoring and improving existing systems to make code faster, cleaner, and more maintainable.Familiarity with modern inference optimization techniques: continuous batching, KV-cache management, sharding strategies, quantization.Domain knowledge in Speech-to-Text (ASR architectures, audio processing, streaming inference) is a plus.Strong Python skills; C++ or Rust experience for kernel-level work is a plus.Deep understanding of distributed training at scale and ML infrastructure best practices.Excellent communication skills and a collaborative mindset to clearly explain complex tradeoffs and prioritize high-impact work.Salary and PerksPay range: $190K - $248KAbout AssemblyAIIndustry-leading Speech AI models to automatically recognize and understand speech.