Software Engineer Intern, Machine Learning Platform (Ad Cloud) at Appier

Taipei, , Taiwan -

Full Time

Start Date

Immediate

Expiry Date

26 Feb, 26

Salary

0.0

Posted On

28 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Java, Machine Learning, Spark, Flink, Kubernetes, Docker, Cloud Platforms, PostgreSQL, ClickHouse, Git, Problem Solving, Team Collaboration, Communication, LLM-based Tools, Monitoring Tools

Industry

IT Services and IT Consulting

Description

【About Appier 】 Appier is a software-as-a-service (SaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information. 【The Impact You'll Make at Appier】 We're looking for a Machine Learning Platform Engineer Intern to join our Machine Learning Platform Team, which powers end-to-end infrastructure for model training, evaluation, deployment, and monitoring at scale. Our platform supports daily execution of hundreds of ML models and processes billions of data records across batch and streaming pipelines. In this role, you'll work alongside experienced engineers to contribute to the core components of our ML platform—including batch processing (Spark), streaming (Flink), job orchestration, and infrastructure tools. You'll gain hands-on experience building scalable ML systems while learning industry best practices and modern development tools including LLM-based programming assistants. 【What You'll Work On】 Contribute to batch (Spark) and streaming (Flink) pipelines that process billions of records daily for ML training and evaluation. Assist in developing and maintaining ML job execution frameworks for training, inference, and post-processing. Work on internal API servers and developer tools to orchestrate ML jobs on Kubernetes. Help maintain data infrastructure using ClickHouse and PostgreSQL. Support platform observability through monitoring tools like Prometheus and Grafana. Collaborate with data scientists, engineers, and senior team members to deliver reliable ML platform capabilities. Learn and apply LLM-based tools (e.g., GitHub Copilot, ChatGPT) to accelerate development, documentation, and debugging. Participate in code reviews and team engineering practices. 【What We're Looking For】 [Minimum Qualifications] Currently enrolled in an undergraduate or graduate program (Bachelor's, Master's, or Ph.D.) in Computer Science, Engineering, or a related field. Strong programming skills in Python and/or Java. Basic understanding of machine learning concepts and ML pipelines. Familiarity with version control systems (Git) and software development practices. Good problem-solving skills and willingness to learn. Ability to work collaboratively in a team environment. Good communication skills. [Preferred Qualifications] Coursework or projects involving distributed systems, data processing, or machine learning. Experience with any of: Spark, Flink, Kubernetes, Docker, or cloud platforms (GCP/AWS). Familiarity with databases such as PostgreSQL, ClickHouse, or similar systems. Experience using LLM-based tools (e.g., GitHub Copilot, ChatGPT) for coding assistance. Previous internship or research experience in machine learning or platform engineering. 【Commitment】 Schedule: 2-5 days per week (16-40 hours) Duration: Minimum 6 months

Responsibilities

Contribute to batch and streaming pipelines that process billions of records daily for machine learning training and evaluation. Assist in developing and maintaining ML job execution frameworks and collaborate with data scientists and engineers to deliver reliable ML platform capabilities.