Senior Platform Engineer

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Requirements:

• Strong expertise in Python and libraries for machine learning and data processing
• Extensive experience with Kubernetes, including deployments, scaling, and management of containerized applications
• In-depth knowledge of AWS services related to computing, storage, and machine learning
• Hands-on experience with building and deploying generative AI and statistical models
• Solid understanding of feature engineering, data preprocessing, and data integration techniques
• Familiarity with MLOps tools and best practices, including automation, monitoring, and orchestration

Responsibilities:

• Develop and maintain scalable and efficient machine learning pipelines capable of processing large volumes of data in real time
• Work independently to deploy, manage, and monitor machine learning models, ensuring high performance and reliability
• Collaborate with product engineering, data science, and ML teams to integrate advanced machine learning features into our products
• Deploy and manage ML models using Kubernetes on AWS, ensuring high availability and low latency for real-time inference
• Implement continuous integration and delivery (CI/CD) processes for machine learning systems, ensuring rapid and safe deployment of features
• Optimize data and feature engineering processes to enhance model performance and reliability
• Monitor and evaluate model performance, making adjustments and improvements as needed
• Ensure compliance with data privacy and security protocols throughout the model lifecycle
• Contribute to the strategic planning and development of ML projects, ensuring alignment with business objectives and technological advancement