Job Description

Architect, build, and maintain end-to-end AI/ML pipelines (data ingestion, preprocessing, training, deployment, predictive analytics / monitoring). Collaborate with data scientists and domain experts to operationalize experimental models, optimizing for performance, scalability, and latency to ensure high-quality datasets. Implement and advocate for AI/MLOps practices (CI/CD for ML, model versioning, feature stores) using modern tools. Optimize model inference for production environments (e.g., using TensorRT, ONNX, pruning, quantization). Write robust, testable, and maintainable code in a collaborative setting using GitHub. Integrate AI models into enterprise systems using APIs and cloud-native services (AWS, Azure). Ensure models meet business objectives while adhering to ethical AI and governance frameworks. Provide technical support and training to users. Troubleshoot and resolve system issues. Participate in business analysis and technical design sessions. Ensure compliance with i...

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