Remote ML Engineer Intern — GenAI Production Pipelines

University of St. La Salle; Philippines; Hybrid; PHP 900,000 - 1,500,000; Full time

Benefits offered by this job

Fully remote

Flexible hours

Direct access to founders

Job summary

AICines is seeking a Machine Learning Engineer to fine-tune and ship generative models powering its AI video and image pipeline. You will work on production-grade systems, not notebooks, in a fully remote, flexible, globally distributed team.

Ideal candidates are current students or recent graduates in CS/ML with Python and ML fundamentals; experience with generative models is a plus. You’ll collaborate directly with founders and senior engineers on live problems.

Qualifications

• Currently studying or recently graduated in Computer Science, Machine Learning, or a related field.
• Working knowledge of Python and ML fundamentals; experience with generative models a plus.
• Comfortable working in a fast-moving, remote-first team.
• Curious, self-directed, and able to communicate technical decisions clearly.
• No prior professional experience required — students, recent graduates, and junior candidates are all encouraged to apply.

Responsibilities

• Fine-tune and ship generative video/image models into production.
• Build the infrastructure that makes generation pipelines run at scale.
• Work on prompt systems and character consistency.
• Fix real model and pipeline issues as the platform grows.
• Collaborate directly with founders and senior engineers on production systems.

Skills

Python

ML fundamentals

Generative models

Remote-friendly

Communication

Fresh grads welcome

Education

CS/ML field

Job description

AICines is seeking a Machine Learning Engineer to fine-tune and ship generative models powering its AI video and image pipeline. You will work on production-grade systems, not notebooks, in a fully remote, flexible, globally distributed team.

Ideal candidates are current students or recent graduates in CS/ML with Python and ML fundamentals; experience with generative models is a plus. You’ll collaborate directly with founders and senior engineers on live problems.