Senior Platform Engineer

Summary

Join AssemblyAI's Research team as a Senior Researcher and contribute to the development of cutting-edge Speech AI models. You will train large-scale models, optimize training code, stay current on AI research, and collaborate with the technology leadership team. This role requires deep learning expertise, experience with JAX/TPUs, and strong Python skills. The ideal candidate will possess a fine-grained understanding of deep learning research and engineering, spanning both software and hardware. AssemblyAI offers a competitive salary and the opportunity to work on impactful projects within a remote, collaborative environment. We are a small but mighty group of startup veterans and experienced AI researchers with over 20 years of expertise in Machine Learning, Speech Recognition, and NLP.

Requirements

• 2+ years of professional experience in deep learning research & development
• Demonstrated experience in all aspects of deep learning model development, including data acquisition and processing, implementation, model training, experimental analysis, and writing inference and evaluation code as an individual contributor
• Hands-on experience with JAX/TPUs and distributed training
• Excellent knowledge of GPU and TPU hardware
• Strong Python programming skills
• Strong written and verbal communication skills for technical matters

Responsibilities

• Train large-scale Speech AI models, including ASR and speech-focused multi-modal LLMs with billions of parameters
• Write and optimize training code for maximum efficiency and memory utilization
• Stay up-to-date on the latest AI research and share insights across the company
• Collaborate with the technology leadership team to prioritize the research and engineering agenda, define project scopes, and lead their execution

Preferred Qualifications

• Experience in training/fine-tuning (multimodal) Large Language Models
• Experience in LLM inference using frameworks like vLLM or JetStream

Benefits

• US Salary Range: $157,500 - $180,000 USD per year
• Fully remote team