Machine Learning Engineer / AI Systems Engineer

Amira Learning is an education technology company using AI to improve literacy outcomes for students and teachers. The Machine Learning Engineer / AI Systems Engineer will design, develop, and operate production machine learning systems involving speech recognition, NLP, LLMs, adaptive learning, and real-time educational assessment. The role also involves building scalable backend services, data pipelines, cloud infrastructure, model validation processes, and technical architectures in collaboration with engineering, data science, and product teams.

Responsibilities:

• Design, develop, and maintain automated educational evaluation and learning systems leveraging speech recognition, NLP, and large language models (LLMs) to assess real‑time user performance and feedback
• Integrate and fine‑tune third‑party AI services, open‑weight LLMs, and proprietary models to deliver adaptive, conversational learning experiences personalized to user proficiency
• Architect and implement end‑to‑end ML pipelines for data extraction, semantic analysis, multi‑label classification, and predictive modeling supporting real‑time content delivery
• Build scalable Python backend services and cloud‑native infrastructure engineered for low‑latency inference in production AI environments
• Conduct rigorous model validation and bias analysis to ensure accuracy, scalability, and reliability across diverse user populations
• Develop distributed data engineering solutions to process, transform, and serve large‑scale educational datasets for model training and real‑time inference
• Collaborate with cross‑functional engineering, data science, and product teams to translate complex business requirements into robust AI architectures
• Author technical design documents, algorithm specifications, and architecture decision records; communicate progress, risks, and trade‑offs to technical and non‑technical stakeholders. Fully remote; work from any U.S. location (no relocation required)

Requirements:

• Master's degree (or foreign equivalent) in Computer Science or a related field and 18 months of experience in the job offered or in a related occupation within a startup environment, involving the design, development, and operation of machine learning–powered services deployed in production