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Machine Learning Engineer
2 months ago
FIS is seeking an experienced and dynamic MLOps engineer to join our team. As a subject matter expert in the development of a Cloud Based solution/product, you will have at least 3 years of experience in Machine Learning & ML OPS and proven experience in deploying models on Azure Cloud.
Key Responsibilities- Participate in daily scrums for developing machine learning solutions, working in an Agile development framework.
- Understand business problems and work with various business and technical stakeholders.
- Perform exploratory data analysis and understand metadata.
- Create and review ML models.
- Understand supervised learning, unsupervised learning, and reinforcement learning.
- Understand generative AI and prompt engineering.
- Fine-tune models.
- Partner with data engineers, ML engineers, developers, and business teams to test models in production.
- Build and maintain operational tools for deployment, monitoring, and analysis of Azure infrastructure and systems.
- Administer and troubleshoot Linux-based, Dockerized, Kubernetes-orchestrated systems.
- Maintain and support the solution post-development.
- Experience with time series forecasting models: ARMA, ARIMA, SARIMA, Vector Auto Regression, Smoothing, Kalman Filtering.
- Anomaly detection: Isolation forests, SVM, Decision Trees, and Ensemble Learning.
- Deep learning basics: RNN, LSTMs, Transformer Architecture, BERT, GPT, Roberta.
- Generative AI prompt engineering: defining and working on prompts, fine-tuning LLMs, RAG.
- Lang Chain: Chain, Prompts, Agents, Vector Stores, Document Loaders.
- Deploying ML models on Cloud: model endpoint deployment, Docker, understanding REST APIs, Bitbucket.
- Cloud Azure Services: Chat GPT Turbo, Azure AI Search, Azure Content Safety, Cosmos DB, Blob Storage, Data Bricks, Azure Kubernetes Services, experience in creating ML pipelines on Azure.
- Good communication skills: listening, comprehending, speaking.
- Understanding of application architecture/microservices: application architecture, microservice-based architecture.
- Programming: Python, SQL; familiar with Python libraries like Scikit-Learn, TensorFlow, Keras, PyTorch, Scikit-Learn, Seaborn, Matplotlib.
- Experience working in the financial industry.
- An opportunity to make your mark in a world-leading global Fintech.
- A flexible hybrid environment with a broad spectrum of opportunities.
- A competitive salary package with medical and personal insurances and employee shareholding.
