Description

Amira Learning is seeking an experienced Machine Learning Engineer to design, deploy, and maintain automated educational evaluation systems using advanced AI technologies like speech recognition, NLP, and LLMs. This role involves integrating and optimizing third-party AI services, building scalable Python backend services on cloud infrastructure, and conducting rigorous model validation to ensure accurate and reliable educational content delivery. The ideal candidate will collaborate with cross-functional teams to create robust AI architectures and contribute to cutting-edge work aimed at improving literacy outcomes globally.

Required Skills

Speech Recognition
Natural Language Processing
Large Language Models
Machine Learning Pipelines
Python Backend Services
Cloud Infrastructure
Distributed Systems
Data Engineering Solutions
Model Validation
Bias Analysis
Performance Optimization
Semantic Analysis
Multi-label Classification
Predictive Modeling
API Services

Additional Information

Required Previous Experiences: 3+ years in ML engineering, AI systems development, or software engineering related occupation, in a startup environment.
Designing, developing, and deploying machine learning and artificial intelligence systems for real-time, production-grade educational or adaptive learning platforms, including speech recognition, natural language processing, and large language model integration.
Architecting scalable Python backend services optimized for low-latency, high-throughput AI inference serving concurrent users on cloud infrastructure.
Applying machine learning techniques — including semantic analysis, multi-label classification, and predictive modeling — to build end-to-end automated evaluation and feedback systems.
Engineering large-scale distributed data systems and cloud-native pipelines for processing, transforming, and serving high-volume datasets for model training and real-time inference.
Conducting model validation, bias analysis, and performance optimization to ensure accuracy, scalability, and reliability across diverse user populations.
Programming in Python, including development of production ML pipelines, API services, and integration of third-party AI services with proprietary models.
Preferred Qualifications: Designing, developing, and deploying machine learning and artificial intelligence systems for real-time, production-grade educational or adaptive learning platforms, including speech recognition, natural language processing, and large language model integration.
Architecting scalable Python backend services optimized for low-latency, high-throughput AI inference serving concurrent users on cloud infrastructure.
Applying machine learning techniques — including semantic analysis, multi-label classification, and predictive modeling — to build end-to-end automated evaluation and feedback systems.
Engineering large-scale distributed data systems and cloud-native pipelines for processing, transforming, and serving high-volume datasets for model training and real-time inference.
Conducting model validation, bias analysis, and performance optimization to ensure accuracy, scalability, and reliability across diverse user populations.
Programming in Python, including development of production ML pipelines, API services, and integration of third-party AI services with proprietary models.

About Amira Learning

Amira Learning

AI reading

Amira Learning offers the first comprehensive AI reading suite designed to help PreK–8 students develop foundational literacy skills and accelerate measurable reading growth.

Founded: 2018

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Machine Learning Engineer at Amira Learning

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About Amira Learning

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