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 seeking a data scientist with experience and skills in deep learning, particularly 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 developing machine learning systems analyzing image and video data, with models developed in Python.
Technologies you might work with include: Python, PyTorch, Keras, TensorFlow, SciKit Learn, Microsoft Azure (Azure Cognitive Services, Azure Machine Learning, Databricks), and Azure DevOps tooling.
What you will work on:
1. Continuous development of our clients’ machine learning platform and products mainly based on Azure.
2. Identifying, creating, and preparing data required for machine learning algorithms.
3. Deploying and maintaining machine learning solutions in production using Agile/SCRUM methodology.
4. 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 in building applications in Python (or R), with real-world experience in NLP (Natural Language Processing) and computer vision (object detection, classification). Familiarity with machine learning libraries like TensorFlow, Keras, PyTorch, etc.
* Experience with Azure cloud technologies, including Azure Databricks.
* Experience with various machine learning algorithms and the end-to-end lifecycle of ML projects.
* Experience with Microsoft Azure DevOps and GIT.
* Strong collaborative skills and a proactive approach to knowledge sharing.
* Experience working in agile teams following practices such as SCRUM.
* Proven experience in implementing deep learning models and using ML development frameworks.
* Extensive use of MLOps CI/CD pipelines, release management on Azure, and experience with MLflow for model orchestration and monitoring.
* Programming skills to analyze large datasets and develop data-driven solutions.
* Experience leading design and development activities within an Agile environment and familiarity with Agile ceremonies.
* Experience working with enterprise and solution architects in a multidisciplinary collaborative environment.
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