Machine Learning Engineer (Intern)

Machine Learning Engineer Intern to join Enterprise Solution Science Team, applying ML to marketing problems. Build and optimize ML infrastructure.

About Appier

Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.

About the role

We are looking for a Machine Learning Engineer Intern to join the Enterprise Solution Science Team.This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data.In this role, you will help bridge the gap between research and production by building and optimizing scalable, high-performance ML infrastructure — including data pipelines, dashboards, and monitoring systems.

We are currently looking for individuals who can commit to an internship schedule of 232 hours) per week. This internship opportunity entails a minimum duration of 6 months, beginning from the present date. We advise prospective applicants to carefully assess their availability for this commitment before submitting their applications.

_* Due to the hybrid work model, this position cannot be fully remote and requires working in the Taiwan office. _

What You’ll Work On

Assist in operating robust ML job execution frameworks for training, inference, and post-processing.
Assist in building and maintaining internal API servers and developer tools to orchestrate ML jobs on Kubernetes (via Argo Workflows, Helm, Terraform).
Assist in implementing data infrastructure and monitoring tools like Prometheus and Grafana.
Create internal tools and services to simplify ML experimentation and production workflows.
Collaborate closely with senior ML engineers and scientists to turn research outputs into user-facing product features

What We’re Looking For

[Minimum qualifications]

Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s degree preferred)
2+ years of experience in ML or engineering
Proficiency in at least one programming language such as Python, Java, or Go, along with solid understanding of data structures and algorithms

[Preferred qualifications]

Impact-driven mindset, strong analytical and problem-solving skills, and a continuous passion for learning cutting-edge technologies.
Familiar in using LLM-powered tools (e.g., Github Copilot, ChatGPT) to boost development productivity
Understanding of core ML and deep learning concepts
Hands-on experience with end-to-end ML workflows and AI system architecture, and familiarity with platforms like Kubeflow, MLflow, or Apache Submarine.
Proficiency with cloud-native ecosystems (e.g., Kubernetes, Helm, Prometheus, Argo Workflows)