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Computer Code ProgrammingI am an applied AI and platform engineer with over 9 years of experience building cloud-native systems and robust MLOps pipelines, with a strong focus on reproducibility, fairness, and reliability in AI training data workflows. My expertise spans reinforcement learning environments, benchmarking, and evaluation metrics, where I have designed and deployed reproducible pipelines to ensure consistent results across varied hardware and experimental conditions. I am skilled in Python, PyTorch, TensorFlow, and automation scripting, and have led code reviews to improve data quality, annotation consistency, and experimental standards. My projects include developing end-to-end automation for model evaluation and reproducible benchmarking, leveraging tools like MLflow, Kubernetes, CI/CD, and observability stacks. I am passionate about advancing best practices in AI data pipelines and collaborating with cross-functional teams to drive high-quality, reliable training data for diverse AI applications.
select a codebase that is a git repository, and ask the model to perform a single task in that codebase.
Master of Technology, Artificial Intelligence and Machine Learning
Bachelor of Technology, Electronics and Communication Engineering
Senior Site Reliability Engineer
DevOps Engineer
