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Manage Model Lifecycle – Track model performance, detect drift, retrain models when necessary, and optimize infrastructure for scalability and cost efficiency.
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- Must Have Skills: Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- - Experience with cloud-based ML platforms (AWS, GCP, Azure).
- - Solid understanding of MLOps tools and practices (CI/CD, model monitoring, retraining).
- - Familiarity with distributed computing and big data tools (Spark, Ray, Dask).
- - Knowledge of responsible AI principles, including fairness, transparency, and accountability.
- Excellent communication skills and ability to present technical concepts to diverse audiences.
- Nice to Have Skills:
- Prior experience in translating ML solutions into measurable business impact
- Deploy and Monitor ML Models – Ensure models are successfully deployed into production environments and continuously monitor their performance and reliability.
Manage Model Lifecycle – Track model performance, detect drift, retrain models when necessary, and optimize infrastructure for scalability and cost efficiency.
Key Skills
Ranked by relevance
cicd
distributed computing
tensorflow
big data
python
cloud
spark
mlops
aws
gcp
ai
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- Posted
- Nov 25, 2025
- Type
- Full-time
- Level
- Entry
- Location
- Sydney
- Company
- XPT Software Australia
Industries
IT Services
IT Consulting
Categories
Engineering
Information Technology
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3 roles aligned with this opportunity
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2026-04-10
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DevOps SRE
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