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# (Full remote)AI Engineer

- **Company:** United World Inc
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Cloud Computing, Continuous Integration, Programming Tools, Middleware, Google Docs, Github, Integrated Development Environments, Python (Programming Language), Machine Learning, Natural Language Processing, Octopus Deploy, Azure Machine Learning, Software Deployment, Software Requirements Analysis, Speech Recognition, Google Cloud, Cloud Platform System, Large Language Models, Technical Debt, Build Tools, Figma, Machine Learning Operations, Discord, Terraform
- **Published:** August 28, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pfuanjlcq3

## About the Role

Languages: Python

 - Cloud Platforms: Google Cloud / AWS / Azure

 - Provisioning Tools: Terraform

 - CI/CD: GitHub Actions / Argo CD

 - Middleware: OpenSearch

 - Documentation: Notion / Google Docs

 - Development Tools: GitHub / Figma

 - Communication Tools: Slack / Discord / Google Meet

 - BI Tools: Redash

[All of the following are required]

 - 2+ years of experience developing and operating ML services within a team

 - Experience with development and operations in cloud environments such as GCP or AWS

 - Expertise in one of the following fields: Machine Learning, Natural Language Processing, Image Recognition, or Speech Recognition

 - Business-level Japanese communication skills / Native-level Japanese proficiency

## Description

As a Machine Learning Engineer on the product team, you will be responsible for developing products centered around LLMs (proprietary/in-house models).

 - Leverage ML technologies, including LLMs, to solve problems and create value for our products.

 - Take ownership of establishing internal systems that integrate machine learning and engineering.

 - Address technical debt to ensure sustainable development.

 - Develop and operate scalable, highly available LLM inference infrastructure.

(Job Overview)

 1. Product Development

 - Handle the end-to-end process for ML-powered features, from requirements definition and value validation to development.

 - Drive continuous improvement based on user feedback and quantitative metrics.

 - Optimize in-house models and integrate them into products.

Optimize models by balancing inference speed and accuracy.

Research and apply model lightweighting techniques.

 2. Leading ML & Engineering Integration

 - Implement internal libraries to facilitate the integration of ML models into products.

 - Establish workflows for efficient production deployment of models.

 - Optimize and refactor product code.

 - Provide technical support to other teams (consulting on architecture and implementation strategies).

 3. MLOps Infrastructure Development & Improvement

 - Design and implement scalable, flexible inference infrastructure.

 - Build systems for continuous model monitoring and performance evaluation.

 - Establish best practices for model operations in production environments.

*Development Environment

We fully utilize cutting-edge AI development tools-such as Claude Code and Devin-while maintaining a strong focus on security.


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