Amira Learning accelerates literacy outcomes by delivering AI-powered reading support. As a leading edtech company, Amira uses speech recognition, natural language processing, and large language models to power 1:1 tutoring and teacher support, trusted by more than 2,000 districts and millions of students worldwide. Essential functions include designing, deploying, and maintaining automated educational evaluation systems that analyze real-time user performance and feedback using speech recognition, NLP, and LLMs. The role also involves integrating, fine-tuning, and optimizing third-party AI services, open-weight LLMs, and proprietary models to power conversational and adaptive learning experiences tailored to individual user proficiency. Other responsibilities include architecting end-to-end ML pipelines for data extraction, semantic analysis, multi-label classification, and predictive modeling for real-time content delivery; building real-time, low-latency Python backend services on cloud infrastructure; performing model validation, bias analysis, and performance optimization; implementing cloud-native data engineering solutions to process large-scale educational datasets for training and inference; collaborating with cross-functional teams to translate business requirements into production-grade AI architectures; and authoring technical design documents and architecture decisions. This is a fully remote role; you can work from any location in the United States with no relocation required. Qualifications include a Master’s degree in Computer Science or related field, and 3

Amira Learning accelerates literacy outcomes by delivering AI-powered reading support. As a leading edtech company, Amira uses speech recognition, natural language processing, and large language models to power 1:1 tutoring and teacher support, trusted by more than 2,000 districts and millions of students worldwide. Essential functions include designing, deploying, and maintaining automated educational evaluation systems that analyze real-time user performance and feedback using speech recognition, NLP, and LLMs. The role also involves integrating, fine-tuning, and optimizing third-party AI services, open-weight LLMs, and proprietary models to power conversational and adaptive learning experiences tailored to individual user proficiency. Other responsibilities include architecting end-to-end ML pipelines for data extraction, semantic analysis, multi-label classification, and predictive modeling for real-time content delivery; building real-time, low-latency Python backend services on cloud infrastructure; performing model validation, bias analysis, and performance optimization; implementing cloud-native data engineering solutions to process large-scale educational datasets for training and inference; collaborating with cross-functional teams to translate business requirements into production-grade AI architectures; and authoring technical design documents and architecture decisions. This is a fully remote role; you can work from any location in the United States with no relocation required. Qualifications include a Master’s degree in Computer Science or related field, and 3