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Horizon Labs

Applied AI Engineer Intern

Posted 3 Hours Ago
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Remote
Hiring Remotely in SG
Internship
Remote
Hiring Remotely in SG
Internship
Prototype and implement AI-enabled workflows and product features; experiment with prompts, model behavior, evaluation methods, and integrations; collaborate cross-functionally to scope and ship solutions; apply structured testing and documentation to improve AI output reliability; research emerging tools, methods, and APIs.
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Job Title: Applied AI Engineer Intern
Location:
Remote
Type: Freelance / Contract-Based
Hours: Part-time / Full-time (During semester / vacation)Job Description

We are seeking an Applied AI Engineer Intern to prototype, build, and improve practical AI-driven features and workflows. You will help turn model capabilities into usable products and internal tools that create real operational or user value.

Preferred Qualifications

  • Currently pursuing or recently completed a relevant degree, ideally from leading universities such as NUS, NTU, or SMU, while still considering strong candidates from other institutions.

  • Strong academic performance, ideally distinction or above, alongside evidence of initiative, ownership, and high-quality execution.

  • Comfortable using AI tools beyond simple chat workflows to accelerate analysis, drafting, research, and execution.

  • High attention to detail and discipline in checking facts, requirements, and deliverables before sharing work.

  • Able to thrive in a fast-moving startup environment with ambiguity, rapid iteration, and cross-functional collaboration.

  • Strong technical fundamentals plus curiosity about using AI to solve practical workflow or product problems.

  • Ability to balance experimentation speed with careful evaluation, testing, and implementation discipline.

Key Responsibilities

  • Prototype and implement AI-enabled workflows, features, or tools that solve concrete user or business problems.

  • Experiment with prompts, model behavior, evaluation methods, and product-facing integrations.

  • Collaborate with product, operations, and engineering teammates to scope and ship applied AI solutions.

  • Use structured testing and documentation to improve reliability, quality, and repeatability of AI outputs.

  • Research emerging tools, methods, and APIs that can improve applied AI execution.

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