Overview
As a Senior Machine Learning Engineer with a bachelor's degree in Computer Science from Columbia University, I bring a solid foundation in the field and a passion for continuous learning to any project. I am authorized for employment as a U.S. citizen without the need for visa sponsorship and I am fully vaccinated against COVID-19.
I have experience designing and implementing efficient algorithms, as well as staying current with the latest technologies and approaches in the field of machine learning. I excel in a cross-functional team environment and possess strong problem-solving, analytical, and communication skills.
Committed to making a positive impact through my work, I value inclusive and diverse workplaces that are open-minded. I bring unique perspectives to my role and appreciate a work environment that values diversity.
TECHNICAL SKILLS
- Software
- Programming: Python, Java, C, C++, Rust, Ruby, SQL, NoSQL, RESTful APIs, GraphQL, unit & integration testing
- Application: React.js, JavaScript, TypeScript, Swift, HTML, CSS, Django, Flask, Node.js, Express, Selenium
- Cloud: GCP, AWS, Azure, Digital Ocean, Netlify
- Tools: Git, VIM, VS Code, Splunk, Confluence, Jira, Bitbucket, GitHub Actions, Docker, Kubernetes, Linux, Shell Scripting
- Machine Learning
- Deep Learning: PyTorch, TensorFlow, Keras, ML Recommender & Ranking Systems, Large Language Models (LLMs), Generative AI, Transformers, BERT, T5, Scikit-learn, NLP, NLTK
- Data: Pandas, Numpy, SciPy, Spark, Hadoop, MapReduce, Tableau
- MLOps: Airflow, MLFlow, YARN, Kubeflow, Jenkins, Argo, CircleCI, GPU
- ML Systems: Kafka, Zookeeper, ETCD, Avro, Parquet, SHAP, LIME, NVIDIA NeMo, CUDA
Education
Columbia University
Bachelor's Degree, Computer Science (September 2015 - May 2020)
Coursework
- Artificial Intelligence with Python
- Natural Language Processing with Python
- Advanced Programming with C/C++
- Algorithmic Trading with Python (audit)
- Data Structures with Java
- Cloud Computing and Big Data in AWS, GCP, and Azure with Python, JavaScript, HTML/CSS
- Introduction to Cryptography
- Fundamentals of Computer Systems
- Linear Algebra
- Building a Technology Startup
- Computer Science Theory
Stanford University
Certificate, Machine Learning Specialization in Supervised, Unsupervised, and Advanced ML Algorithms (April 2023)
Coursework
- Supervised Learning: Regression and Classification
- Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn
- Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression
- Unsupervised Learning: Clustering, Anomaly Detection, Recommender Systems, Deep Reinforcement Learning, Collaborative Filtering, Content-Based Deep Learning
- Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection
- Build recommender systems with a collaborative filtering approach and a content-based deep learning method
- Build a deep reinforcement learning model
- Advanced Machine Learning Algorithms: Multi-Class Classification in Neural Networks with TensorFlow, Best Practices in Machine Learning Development, Random Forests, Boosted Trees, Regression Trees, XGBoost
- Build and train a neural network with TensorFlow to perform multi-class classification
- Apply best practices for machine learning development so that your models generalize to data and tasks in the real world
- Build and use decision trees and tree ensemble methods, including random forests and boosted trees
Experience
American Express
Senior Machine Learning Engineer (March 2024 - Present) Phoenix, Arizona - Full-time
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Spearhead initiatives to enhance AI/ML system security, focusing on the development and integration of advanced safety controls and stress-testing methodologies
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Design and implement comprehensive AI/ML security processes, including secure model development life cycles and robustness evaluations, to protect against adversarial threats and ensure the responsible use of large language models
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Establish and oversee AI/ML application security standards, contributing to a secure and innovative technology environment
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Collaborate across departments to align security practices with business objectives and regulatory compliance, leveraging expertise in software engineering, machine learning, and cloud technologies to promote the adoption of trustworthy AI practices
Data Engineer II, Machine Learning (May 2022 - March 2024) Phoenix, Arizona - Full-time
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Developed a sophisticated GPT-3 LLM API powered chatbot to interpret user text inputs into SQL queries, enhancing user engagement and operational efficiency by 75% by automating data visualization tasks
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Engineered an NER NLP model for customer data extraction from identity documents, reducing manual processing by 80%
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Created an Isolation Forest anomaly detection ML model, improving customer experience by 25% in product purchases
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Improved data quality with Tableau and Spark, increasing reporting accuracy by 40% and streamlining data management