Machine Learning Engineer / AI Systems Engineer

Amira Learning is an AI-powered literacy platform that uses speech recognition, neuroscience, and personalized tutoring to improve student reading outcomes. The Machine Learning Engineer / AI Systems Engineer will design, develop, and operate production machine learning systems using speech recognition, NLP, LLMs, scalable data pipelines, and cloud-native infrastructure. The role also includes model validation, bias analysis, cross-functional collaboration, and technical documentation.

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

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