Remote ML Engineer - Real-Time Educational AI Systems

Amira Learning; Town of Texas (WI); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, and vision benefits

401(k) with company matching

Flexible time off

Stock options

Job summary

Amira Learning is seeking a skilled ML Engineer to design and deploy real-time AI systems for an adaptive literacy platform. You will build scalable Python backends, integrate NLP and speech recognition, and optimize models for low-latency inference in production.

We offer a fully remote role, with the flexibility to work from anywhere in the United States. The ideal candidate holds a Master’s degree and 3+ years of ML engineering experience in a startup environment.

Qualifications

• Design, develop, and deploy ML/AI systems for real-time educational platforms.
• Experience with speech recognition, NLP, and LLM integration.
• Architect scalable Python backend services for low-latency inference.
• Experience building cloud-native data pipelines.

Responsibilities

• Design, deploy, and maintain automated evaluation systems using NLP and ML.
• Integrate third-party AI services and open-weight LLMs.
• Build end-to-end ML pipelines for real-time content delivery.
• Ensure sub-second inference at scale on cloud infrastructure.
• Collaborate with cross-functional teams and document architecture decisions.

Skills

ML engineering

AI systems

Python backend

NLP

Speech recognition

Low-latency

Cloud infrastructure

Data pipelines

Distributed systems

Team collaboration

Education

Master’s degree in Computer Science or related field

Tools

Python

LLMs

APIs

Cloud services

Job description

Amira Learning is seeking a skilled ML Engineer to design and deploy real-time AI systems for an adaptive literacy platform. You will build scalable Python backends, integrate NLP and speech recognition, and optimize models for low-latency inference in production.

We offer a fully remote role, with the flexibility to work from anywhere in the United States. The ideal candidate holds a Master’s degree and 3+ years of ML engineering experience in a startup environment.