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About The Opportunity
Join a hands-on engineering internship designed for Python-savvy students and early-career developers who want production experience delivering AI-enabled software. You will work with cross-functional teams to prototype models, build data pipelines, and integrate ML into services—gaining mentorship and real product-facing engineering exposure.
Role & Responsibilities
- Prototype and iterate on Python-based ML models for NLP, CV, or tabular tasks and validate performance with experiments and metrics.
- Build and maintain data ingestion and preprocessing pipelines using NumPy and Pandas; ensure data quality and reproducibility.
- Wrap models as lightweight services or APIs (Flask/FastAPI) and collaborate on integration with backend systems.
- Use version control (Git) and follow CI practices to produce clean, testable code; write unit tests and reproducible notebooks.
- Containerize experiments using Docker and assist with basic deployments to cloud instances or VM-based environments.
- Document experiments, present results to engineering stakeholders, and incorporate feedback into successive iterations.
Must-Have
- Proficiency in Python for scripting and model development
- Experience with one or more ML frameworks: PyTorch or TensorFlow
- Hands-on use of data libraries: NumPy and Pandas
- Familiarity with scikit-learn for baseline modeling and evaluation
- Practical Git experience and basic unit testing practices
- Ability to work on-site in Australia for the internship duration
- Experience containerizing apps with Docker
- Exposure to building APIs with Flask or FastAPI
- Familiarity with cloud compute environments (AWS / GCP / Azure)
- Currently pursuing or recently completed a degree in Computer Science, Engineering, Data Science, or related discipline
- Portfolio of projects or GitHub demonstrating Python and ML work (notebooks, model code, small deployed demos)
- Strong problem-solving mindset and eagerness to learn production engineering practices
- Mentorship from senior engineers and exposure to full ML product lifecycle
- On-site, collaborative environment with structured learning goals and evaluation
- Opportunity to convert to full-time roles based on performance and business needs
Note: This is a paid internship.Skills: tensorflow,git,pytorch,pandas,numpy,python,docker
Key Skills
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