Senior Research Engineer

Job not on LinkedIn

🔥 0 minutes ago

🗽 New York – Remote

🗽 New York – Remote

💵 $270k - $310k / year

⏰ Full Time

🟠 Senior

📚 Research Engineer

👻 Ghost score 0%

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AssemblyAI

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📣 Marketing

📦 Logistics

💰 $30M Series B on 2022-07

Consulting • Marketing • Logistics

AssemblyAI is an API platform specializing in state-of-the-art AI models, particularly in the field of speech recognition and understanding. The company closely monitors advancements in AI research to enhance its production-ready models. Developers and product teams leverage AssemblyAI's API for various applications, including transcription, conversation intelligence, summarization, and audio/video content moderation. The introduction of their framework, LeMUR, allows users to effectively apply powerful language models to transcribed speech, further broadening the capabilities of their offerings.

📋 Description

• Raise the team's experimental velocity by making experiment launches, trustworthy measurement, and next-step decisions faster • Maintain and evolve the JAX training framework for scalable, efficient large-scale distributed TPU training • Investigate model-data quality issues, build tooling to surface them, and turn findings into measurable accuracy gains • Analyze production-model accuracy and build evaluation harnesses to identify customer-impacting improvements • Translate research prototypes into production-ready systems while refactoring and modernizing architectures and infrastructure • Optimize production inference for speech language models using serving-architecture improvements, quantization, and speculative decoding • Investigate and resolve performance bottlenecks from low-level kernels such as XLA and Pallas through high-level system design • Partner with researchers, infrastructure, and production engineering to trace problems and ship durable fixes • Train models, run evaluations, and analyze data as needed

🎯 Requirements

• Expert-level proficiency with JAX and TPUs, including Flax, Optax, and the XLA compilation pipeline • Strong experience optimizing inference systems for production, ideally with LLMs or speech models • Deep understanding of distributed training at scale, modern deep learning systems, and ML infrastructure best practices • Familiarity with continuous batching, KV-cache management, sharding strategies, and quantization • Strong Python skills • C++ or Rust experience for kernel-level work is a plus • Excellent communication and a collaborative mindset • Domain knowledge in Speech-to-Text, including ASR architectures, audio processing, and streaming inference, is a bonus