Machine Learning Engineer / AI Systems Engineer

About Us: Amira Learning accelerates literacy outcomes by delivering the latest reading and neuroscience with AI. As the leader in third-generation edtech, Amira listens to students read out loud, assesses mastery, helps teachers supplement instruction and delivers 1:1 tutoring. Validated by independent university and SEA efficacy research, Amira is the only AI literacy platform proven to achieve gains surpassing 1:1 human tutoring, consistently delivering effect sizes over 0.4. Rooted in over thirty years of research, Amira is the first, foremost, and only proven Intelligent Assistant for teachers and AI Reading Tutor for students. The platform serves as a school district’s Intelligent Growth Engine, driving instructional coherence by unifying assessment, instruction, and tutoring around the chosen curriculum. Unlike any other edtech tool, Amira continuously identifies each student’s skill gaps and collaborates with teachers to build lesson plans aligned with district curricula, pulling directly from the district’s high-quality instructional materials. Teachers can finally differentiate instruction with evidence and ease, and students get the 1:1 practice they specifically need, whether they are excelling or working below grade level. Trusted by more than 2,000 districts and working in partnership with twelve state education agencies, Amira is helping 3.5 million students worldwide become motivated and masterful readers. Essential Functions: Design, deploy, and maintain automated educational evaluation systems leveraging speech recognition, natural language processing (NLP), and large language models (LLMs) to analyze and assess real-time user performance and feedback. Integrate, fine-tune, and optimize third-party AI services, open-weight LLMs, and proprietary machine learning models to power conversational and adaptive learning experiences tailored to individual user proficiency. Architect and build end-to-end machine learning pipelines encompassing data extraction, semantic analysis, multi-label classification, and predictive modeling for real-time educational content delivery. Design, develop, and maintain AI/ML systems purpose-built for real-time, low-latency educational platforms serving concurrent users at scale. Architect scalable Python backend services deployed on cloud infrastructure, engineered specifically for sub-second inference in production AI applications. Conduct rigorous model validation, bias analysis, and performance optimization to ensure accuracy, scalability, and reliability of machine learning systems across diverse user populations. Implement cloud-native data engineering solutions utilizing distributed systems and databases 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, production-grade 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). Qualifications (Education and Experience): Master’s degree in Computer Science or related field. 3+ years in ML engineering, AI systems development, or software engineering related occupation, in a startup environment. Qualifying experience must include: 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. Benefits: Competitive Salary Medical, dental, and vision benefits 401(k) with company matching Flexible time off Stock option ownership Cutting-edge work The opportunity to help children around the world reach their full potential Commitment to Diversity: Amira Learning serves a diverse group of students and educators across the United States and internationally. We believe every student should have access to a high-quality education and that it takes a diverse group of people with a wide range of experiences to develop and deliver a product that meets that goal. We are proud to be an equal opportunity employer. The posted salary range reflects the minimum and maximum base salary the company reasonably expects to pay for this role. Salary ranges are determined by role, level, and location. Individual pay is based on location, job-related skills, experience, and relevant education or training. We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, ancestry, national origin, sex, sexual orientation, gender identity or expression, age, disability, medical condition, pregnancy, genetic information, marital status, military service, or any other status protected by law.