Must have a Baseline clearance or above.
The Department has undertaken an initiative to improve its biosecurity risks under the recently established Digital Reform Division. It aims to develop an Enterprise Pest Management system and integrate it with the department’s critical biosecurity information system.
The department is looking for Data Scientists that can work across the Azure technology stack to deliver outcomes that improve risk management capabilities across the cargo pathway and support the movement of shipping containers of imported goods into Australia.
We are looking for a data scientist with experience and skills in deep learning working with computer vision/image recognition or Natural Language Processing (NLP), as well as experience or a desire to learn the Microsoft Azure platform.
The focus will be on machine learning systems analysing image and video data and models developed in Python.
Technologies you might work with: Python PyTorch , Keras , Tensorflow, SciKit Learn Microsoft Azure (Azure Cognitive Services, Azure Machine Learning, Databricks), ALM Azure DevOps tooling
What you will work on:
- Continuous development of our clients’ machine learning platform and products based on mainly Azure
- Identifying, creating and preparing data required for machine learning algorithms
- Deploying and maintaining machine learning solutions in production Using Agile/SCRUM methodology
- Depending on your experience you might work on custom machine learning solution architecture, design, definition and implementation
As the ideal candidate you have:
- Experience with Python scientific computing libraries
- Advanced experience with building applications in one of the major languages, preferably Python (alternatively R) Real life experience in NLP (Natural Language processing) and Computer vision (object detection, classification) Familiar with machine learning libraries like Tensorflow, Keras, PyTorch and similar
- Experience with Azure cloud technologies including Azure Databricks
- Experience with other machine learning algorithms and end to end life cycle of Machine Learning projects
- Experience Microsoft Azure DevOps, and GIT.
- Strong collaborative attributes and a proactive approach to sharing knowledge amongst peers.
- Experience working in an agile team with agile practices e.g., SCRUM.
- Proven experience in implementing Machine Learning models (e.g Deep Learning), ML development frameworks like Tensorflow, Pytorch, scikit learn etc.
- Extensive use of MLOPS CI / CD and release management on Azure and Experience with MLflow for model orchestration and monitoring.
- Programming skills to collect, analyze, and interpret large data sets to develop data-driven solutions for business challenges.
- Experience in leading the design and development activities using Agile product development environment and familiarity with Agile ceremonies.
- Experience in working with the Enterprise and solution architects. Experience in the multi-disciplinary collaborative environment.