AI/ML Python Engineer - Model Development & MLOps

Appsytec; City of Melbourne; On-site; AUD 90,000 - 150,000; Full time

Job summary

Appsytec in Melbourne is seeking an experienced Python Developer to join the AiLECS Lab collaboration with Monash University and the Australian Federal Police. You will develop and optimise AI/ML models, work with large datasets, and collaborate across data science, engineering and research.

Responsibilities include building ML models, implementing algorithms from research, creating robust APIs, and applying MLOps in a collaborative, Agile environment.

Qualifications

• Minimum 2 years' experience in Python software development.
• Experience developing and/or fine-tuning machine learning models.
• Experience developing REST APIs and integrating applications.
• Familiarity with CI/CD, version control and software testing.
• Experience working with Agile methodologies.

Responsibilities

• Develop and optimise machine learning models and applications using Python.
• Build and fine-tune ML models using frameworks such as PyTorch, TensorFlow, Hugging Face and Ultralytics.
• Implement machine learning algorithms from research papers into robust and scalable software.
• Evaluate and benchmark model performance using appropriate metrics.
• Clean, prepare and augment large datasets for model development.
• Develop APIs and integrate AI systems with existing applications and platforms.
• Apply MLOps practices to support model development, evaluation and deployment.
• Work within Agile development environments using tools such as GitLab, GitHub or Azure DevOps.

Skills

Python

REST APIs

CI/CD

Agile methodologies

Git

Software testing

Tools

PyTorch

TensorFlow

Hugging Face

Ultralytics

Job description

Appsytec in Melbourne is seeking an experienced Python Developer to join the AiLECS Lab collaboration with Monash University and the Australian Federal Police. You will develop and optimise AI/ML models, work with large datasets, and collaborate across data science, engineering and research.

Responsibilities include building ML models, implementing algorithms from research, creating robust APIs, and applying MLOps in a collaborative, Agile environment.