Cloud Based MLOps Engineer

2 months ago

Sydney, New South Wales, Australia FIS Australia Full time

About the Role

FIS is seeking an experienced and dynamic MLOps engineer to join our team. As a key member of our Cloud Solutions group, you will be responsible for developing and deploying machine learning models on Azure Cloud.

Key Responsibilities:

  • Participate in daily scrums to develop machine learning solutions, working in an agile development framework.
  • Understand business problems and work with various stakeholders to develop effective solutions.
  • Perform exploratory data analysis and understand metadata.
  • Create and review ML models, with a focus on supervised learning, unsupervised learning, and reinforcement learning.
  • Partner with data engineers, ML engineers, developers, and business teams to test models in production.
  • Briefly, you will be responsible for the entire ML lifecycle, from data preparation to deployment and maintenance.

Requirements:

  • Experience with time series forecasting models, including ARMA, ARIMA, SARIMA, Vector Auto regression, Smoothing, and Kalman Filtering.
  • Experience with anomaly detection, including Isolation forests, SVM, Decision Trees, and Ensemble Learning.
  • Deep learning basics, including RNN, LSTMs, Transformer Architecture, BERT, GPT, and Roberta.
  • Generative AI prompt engineering, including defining and working on prompts, fine-tuning LLMs, and RAG.
  • Deploying ML models on Cloud, including model endpoint deployment, Docker, REST APIs, and Bitbucket.
  • Cloud Azure Services, including Chat GPT 3.5 Turbo, Azure AI Search, Azure Content Safety, Cosmos DB, Blob storage, Data Bricks, and Azure Kubernetes services.
  • Good communication skills, including listening, comprehension, and speaking.
  • Understanding of application architecture and microservices, including application architecture and microservice-based architecture.
  • Programming skills, including Python, SQL, and familiarity with Python libraries such as Scikit-learn, TensorFlow, Keras, PyTorch, Scikit-learn, Seaborn, and Matplotlib.

What We Offer:

  • An opportunity to work on challenging and relevant issues in financial services and technology.
  • A flexible hybrid environment with a broad spectrum of opportunities.
  • A competitive salary package with medical and personal insurances and employee shareholding.

Added Bonus:

  • Experience working in the financial industry.

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