I'm a skilled staff-level Machine Learning Engineer with a strong foundation in Software Engineering, Data Engineering, and MLOps. With hands-on experience building end-to-end machine learning pipelines, I specialize in designing scalable data architectures, deploying robust ML models, and automating workflows using MLOps best practices. Passionate about creating impactful AI solutions, I leverage my expertise in Python, cloud services, and DevOps tools to bridge the gap between data science experimentation and production deployment. My goal is to deliver reliable and efficient machine learning systems that drive business value.
Python, PyTorch, TensorFlow, Keras, Neural Networks, Deep Learning, Machine Learning Pipelines, Python Data Structures, Regression, Classification, Algorithmic Trading, Financial Modeling
CNNs, RNNs, Transformers, Attention Mechanisms, Temporal Conv Networks, Autoencoders, Bayesian Neural Networks, ARIMA, Structural Time Series
Photon: Machine Learning Framework
A machine learning framework that extends the functionality of other frameworks such as TensorFlow & Keras. Photon ML is built to apply neural network and ensemble modeling techniques for deep learning financial algorithms. The framework supports the entire lifecycle of a machine learning project including data preparation, model development, training, monitoring, evaluation and deployment.
Dyson: Modeling Research & Development
An evolving collection of data models and algorithms used to model financial markets including equities, options, futures and crypto assets. The project has grown from only traditional statistical modeling to Machine Learning based modeling which includes deep neural networks and probabilistic reasoning networks.
Maxwell: Machine Learning Preprocessing & Pipelines
A set of custom libraries to handle the unique characteristics of acquisition, preparation and storage of financial market data. These libraries include data connectors (WebSockets/RESTful APIs) to access the data, detect anomalies in hundreds of millions of data points, then cleanse and pre-process to provide high-integrity data modeling. Also included is a set of tools for domain specific feature engineering and labeling of financial market data.
Coding Challenges
A repo of some of the coding challenges I have participated in.
sequenzia.com
appliedtheta.io
linkedin.com/in/sequenzia
stephen@sequenzia.com
My Amateur Astronomy IG