Machine Learning OPS engineer

Position: Machine Learning OPS engineerLocation: SydneyDuration: 6 monthsWe are seeking a highly skilled and motivated Machine Learning Engineer with deep expertise in statistical modeling, experimental design, and modern ML development practices. The ideal candidate will have hands-on experience in building, deploying, and maintaining scalable ML solutions using cloud platforms and MLOps frameworks.Key Responsibilities:Design, develop, and deploy machine learning models using Python and modern ML frameworks.Apply statistical modeling and experimental design to solve complex business problems.Work with cloud platforms such as AWS SageMaker, Google Vertex AI, and Azure ML for scalable model training and deployment.Implement MLOps best practices including CI/CD pipelines for ML, model versioning, monitoring, and automated retraining.Handle large-scale data processing using distributed computing frameworks like Apache Spark, Ray, and Dask.Perform advanced feature engineering and ensure model interpretability, fairness, and compliance with responsible AI principles.Translate complex ML solutions into actionable business insights and communicate findings effectively to both technical and non-technical stakeholdersDeploy and Monitor ML Models – Ensure models are successfully deployed into production environments and continuously monitor their performance and reliability. Automate ML Pipelines – Build and maintain automated workflows for data processing, model training, testing, and deployment using CI/CD practices. Manage Model Lifecycle – Track model performance, detect drift, retrain models when necessary, and optimize infrastructure for scalability and cost efficiency. 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