AI Technical Writer / Machine Learning Documentation Specialist / Developer Documentation Writer

BEACON BRIGHT ORGANISATION; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

BEACON BRIGHT ORGANISATION is seeking a technical writer to create clear AI/ML developer documentation in Singapore. You will work with engineers, data scientists, product managers, and support teams to translate complex concepts into practical guidance for developers and business readers.

You will develop API references, setup instructions, tutorials, and code examples, while maintaining docs as products evolve. A portfolio of technical docs is highly valued.

Qualifications

• Bachelor's degree or equivalent in technical communication, CS, IT or related field.
• Experience in technical writing, developer docs, software docs, or ML content.
• Strong writing and editing skills, able to explain technical subjects clearly.
• Familiarity with AI/ML concepts, including models, datasets, evaluation, deployment.
• Collaborate with engineers and subject matter experts to verify information.
• Portfolio of technical documentation, tutorials, or developer education materials is beneficial.

Responsibilities

• Create API references, setup instructions, tutorials, code samples, and model guides.
• Document authentication, requests/responses, SDKs, configuration, error handling, deployment.
• Maintain and organize docs as products and models change; follow style guidelines.
• Coordinate reviews with technical teams to verify accuracy and completeness.
• Ensure accessibility and usability; support responsible AI and security guidance as needed.

Skills

Technical Writing

Developer Docs

AI/ML Content

Markdown

Git

Docs-as-Code

Content Management

Editing

Education

Bachelor’s degree in technical communication or related field

Tools

Markdown

Git

CMS

Docs-as-Code

Job description

Creates clear, accurate documentation that helps developers, customers, and internal teams understand and use AI and machine learning products. Works with engineers, data scientists, product managers, support teams, and subject matter experts to gather information about system behavior, product capabilities, workflows, and limitations. Turns technical details into practical guidance for the intended audience.

Develops and maintains materials such as API references, setup instructions, tutorials, code examples, model guides, architecture overviews, troubleshooting steps, release notes, and frequently asked questions. Organizes documentation so readers can find information easily and complete tasks without unnecessary assistance. For developer-focused content, may document authentication, requests and responses, SDKs, configuration, error handling, deployment, and integration patterns.

For AI and machine learning topics, explains concepts such as model inputs and outputs, data requirements, evaluation methods, prompts, retrieval, deployment, and performance considerations. Takes care to describe what a system can and cannot do, identify relevant assumptions, and document known limitations. May test procedures and code samples directly to confirm that they work as written, and coordinates reviews with technical teams to verify accuracy.

Maintains documentation as products, APIs, models, and workflows change. Establishes or follows style and terminology guidelines, manages content through review and publication workflows, and tracks feedback to identify gaps or confusing material. May also support documentation for responsible AI practices, privacy and security guidance, model evaluation, or operational procedures, depending on the product and organization.

Qualifications

Role Description

Creates clear, accurate documentation that helps developers, customers, and internal teams understand and use AI and machine learning products. Works with engineers, data scientists, product managers, support teams, and subject matter experts to gather information about system behavior, product capabilities, workflows, and limitations. Turns technical details into practical guidance for the intended audience.

Develops and maintains materials such as API references, setup instructions, tutorials, code examples, model guides, architecture overviews, troubleshooting steps, release notes, and frequently asked questions. Organizes documentation so readers can find information easily and complete tasks without unnecessary assistance. For developer-focused content, may document authentication, requests and responses, SDKs, configuration, error handling, deployment, and integration patterns.

For AI and machine learning topics, explains concepts such as model inputs and outputs, data requirements, evaluation methods, prompts, retrieval, deployment, and performance considerations. Takes care to describe what a system can and cannot do, identify relevant assumptions, and document known limitations. May test procedures and code samples directly to confirm that they work as written, and coordinates reviews with technical teams to verify accuracy.

Maintains documentation as products, APIs, models, and workflows change. Establishes or follows style and terminology guidelines, manages content through review and publication workflows, and tracks feedback to identify gaps or confusing material. May also support documentation for responsible AI practices, privacy and security guidance, model evaluation, or operational procedures, depending on the product and organization.

• Bachelor’s degree in technical communication, computer science, information technology, linguistics, or a related field; equivalent experience may be considered
• Experience in technical writing, developer documentation, software documentation, or machine learning content
• Strong writing and editing skills, with the ability to explain technical subjects clearly and accurately
• Familiarity with AI and machine learning concepts, including models, datasets, evaluation, and deployment
• Ability to work with engineers and subject matter experts to gather, verify, and organize technical information
• Experience documenting APIs, SDKs, software workflows, or developer tools is an asset
• Basic proficiency in a programming language such as Python or JavaScript and confidence testing code examples
• Familiarity with documentation tools, Markdown, Git, content management systems, or docs-as-code workflows
• Strong attention to detail, especially when checking procedures, terminology, examples, and product behavior
• Ability to organize information for different audiences, including developers, technical users, and business readers
• Good project-management skills and ability to manage documentation updates alongside product releases
• Comfortable identifying unclear source material and asking focused questions to resolve gaps
• Knowledge of accessibility, information design, and content usability is beneficial
• Experience with cloud services, APIs, generative AI, or developer platforms is an asset
• A portfolio of technical documentation, tutorials, or developer education materials is beneficial for some positions