AI/ML Data Scientist Intern: Build & Scale Production Models

Infineon; Western Australia; On-site; AUD 34,000 - 48,000; Part time

Job summary

Infineon Technologies Australia is seeking an AI/Data Science Intern to support production AI apps and explore new use cases across computer vision, predictive modeling, anomaly detection, and GenAI where applicable. You will enhance data pipelines, monitor models, and collaborate with cross-functional teams to ensure deployment readiness and scalable AI solutions across sites.

The role offers hands-on learning in model monitoring, data engineering, and KPI evaluation while developing practical

Qualifications

• Education: Bachelors/Masters in Data Science or related field.
• ML fundamentals: training/evaluation, overfitting, cross-validation.
• Programming: Python; SQL for data extraction and analysis.
• Version control: Git and reproducible workflows.
• MLOps & containerization: Docker/Kubernetes basics.
• GenAI & agentic AI exposure: GenAI/LLMs and prompting.
• Learning mindset & collaboration: proactive and team-focused.

Responsibilities

• Sustain and improve production AI applications across sites.
• Explore and prototype new AI use cases aligned with KPIs.
• Enhance data pipelines and preprocessing for quality and repeatability.
• Evaluate and document model performance, risks, and limitations.
• Collaborate with cross-functional teams and share knowledge via demos.
• Support deployment readiness, scaling of AI solutions across processes.
• Gain hands-on experience in monitoring, maintenance, and deployment of models.

Skills

Python

SQL

ML fundamentals

Git

GenAI & LLMs

Containerization

Collaboration

Problem solving

Education

Bachelors/Masters in Data Science or related field

Tools

Docker

Kubernetes

Git

Job description

Infineon Technologies Australia is seeking an AI/Data Science Intern to support production AI apps and explore new use cases across computer vision, predictive modeling, anomaly detection, and GenAI where applicable. You will enhance data pipelines, monitor models, and collaborate with cross-functional teams to ensure deployment readiness and scalable AI solutions across sites.

The role offers hands-on learning in model monitoring, data engineering, and KPI evaluation while developing practical