Remote Kotlin Engineer for AI Training Content and Review

SME Careers; Indonesia; Remote; IDR 110,208,000 - 220,416,000; Full time

Job summary

SME Careers is seeking a remote, hourly-paid Kotlin Engineer to review AI-generated responses and generate high-quality Kotlin-focused content. You will evaluate reasoning quality and step-by-step problem solving, assess for accuracy, clarity, and prompt adherence, and craft expert explanations and model solutions.

Responsibilities include developing detailed prompts, ranking AI responses to improve accuracy and fluency, and testing models for biases and reliability across use cases.

Qualifications

• 2+ years of hands-on Kotlin development experience.
• Strong understanding of Kotlin null safety, coroutines, and functional idioms.
• Professional software engineering experience using Kotlin for Android or backend services.
• Minimum Bachelor’s degree in Computer Science or a closely related field.

Responsibilities

• Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
• Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
• Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.

Skills

Kotlin development

Kotlin null safety

Coroutines

Functional idioms

Android/backend Kotlin

LLMs for coding

English writing

Problem solving

Education

Bachelor's degree in Computer Science

Tools

Ktor

Android Jetpack

Job description

SME Careers is seeking a remote, hourly-paid Kotlin Engineer to review AI-generated responses and generate high-quality Kotlin-focused content. You will evaluate reasoning quality and step-by-step problem solving, assess for accuracy, clarity, and prompt adherence, and craft expert explanations and model solutions.

Responsibilities include developing detailed prompts, ranking AI responses to improve accuracy and fluency, and testing models for biases and reliability across use cases.