ML Engineer, Software Engineer

AI/ML Development San Diego, California, United States

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Summary

Hi, I'm a results-driven Machine Learning Engineer, Software Engineer, and Data Scientist with a passion for leveraging cutting-edge technologies to solve complex problems. With a Master's degree in Computer Science - Artificial Intelligence from UC San Diego, I possess expertise in machine learning, deep learning, and reinforcement learning.

As a Graduate Student Researcher at the San Diego Supercomputer Center, I reduced fire detection time by 22% by implementing a multi-modal architecture combining images and weather data. I automated the processing of 10 million rows of historical weather data and halved the model training time using multi-GPU training. Additionally, I managed the ML lifecycle using MLflow, improving productivity.

At Cisco Systems, I automated the bug scrub process using NLP and ML, reducing bug processing time by 80%. I also decreased regression testing time on customer networks by 90%, enhancing customer response time. I reported critical network design issues during scale and feature testing for Verizon's networks.

During my internship at Red Hat, I enhanced the resiliency of customer applications on OpenShift by adding new features and improving code security. I utilized Kubernetes and Docker to devise node outage scenarios and chaos scenarios based on traffic shaping.

I am proficient in Python, Java, C++, TensorFlow, PyTorch, and skilled in cloud platforms such as AWS Lambda, S3, SageMaker. My expertise extends to data engineering, data visualization, statistical analysis, and machine learning systems.

Expectations

In my new job, I look for challenging and innovative projects that combine machine learning engineering and software development. I want a strong technical environment that fosters learning and collaboration. A balance between research and implementation is crucial to me. I strive to make a tangible impact and seek a collaborative, agile environment. Professional development and growth opportunities matter, as well as ethical considerations in AI development.