As both a technical lead and individual contributor specializing in machine learning and data-centric systems, I have driven technical initiatives and led a small but diverse team of software, machine learning, and data engineers to deliver innovative solutions that align with best practices and business objectives. My focus has been on fostering collaboration, promoting technical excellence, and enhancing team capabilities to achieve impactful results in AI and data projects.

• Developed a robust MLOps framework with tools like Ray, Optuna, Weights & Biases, and MLflow, optimizing the entire ML lifecycle from model training to deployment. This framework significantly accelerated deployment, improved model reproducibility, and strengthened data lineage while reducing the complexity and time required for deploying to production.
• Leveraged tools such as Torch Profiler and Nvidia Nsight to diagnose and address inefficiencies in PyTorch-based deep learning anomaly detection models. By refactoring the data loader and rearchitecting key layers, achieved a reduction in training times of over 94%.
• Built highly distributed, functional programming-based data pipelines with Apache Airflow and Dask to support complex machine learning and analytics workflows, enabling efficient, scalable data processing and seamless integration of diverse data sources for enhanced throughput and reliability
• Principal architect of an Apache Arrow-native Data Lakehouse using S3 and PostgreSQL for efficient management of time series data, metadata, and a machine learning feature store, enabling seamless access, high-performance queries, and scalable analytics.
• Refactored a PostgreSQL database for improved normalization, performance, and scalability, reducing query response times by over 95%. Optimizations streamlined data access, minimized redundancy, and enabled efficient scaling to meet higher workloads.
• Deployed and managed a secure, scalable Kubernetes cluster on AWS GovCloud to support ML and data visualization platforms, ensuring high availability, automated scaling, and efficient resource management in a compliant environment.

Develop analytic opportunities through a suite of frameworks and models designed to expedite development and uphold the integrity of applied AI/ML models tailored to the specific demands of financial markets. Originally built for internal purposes, many of these models and frameworks are now available as open-source resources.

• Developed the entire technology strategy, roadmap, and solutions using agile software development.
• Developed several python-based frameworks and libraries.
• Utilized Machine Learning algorithms to produce financial models and algorithmic trading systems.
• Built advanced data pipelines to handle data from various market sources and time resolutions.
• Standardized codebases to utilize leading data science frameworks like TensorFlow, PyTorch, Keras, NumPy, and Pandas.
• Provided Machine Learning based consulting, design and development to other companies.

Worked with senior leadership to shape technology strategies for data management, acting as consultant, architect, and lead developer on solution design and development using diverse technologies and agile methods.

• Designed and developed complex data integrations across multiple business applications.
• Deployed many SQL/No SQL databases and designed custom data schemas.
• Designed and deployed data pipeline architectures across multiple data sources and developed ETL processes.
• Full-stack development of several custom web-based applications and reporting systems.
• Designed and implemented highly available virtual infrastructures, fully cloud-based and hybrid co-lo/cloud.

Collaborated with senior leadership to align technology solutions with business needs, serving as consultant, DBA, and lead developer on critical IT infrastructure projects.

• Set up, deployed, and managed many MS SQL Servers and databases for both custom and 3rd party applications. 
• Designed and developed complex data integrations across multiple business applications.
• Developed and deployed web-based interfaces for access to back-end data sources.
• Managed a small team of network engineers and developers.

Provided full-stack IT consulting, support, and development for small to medium-sized companies in various industries.

• Managed a team of 15 technicians and network engineers.
• Set up, deployed, and managed many MS SQL Servers and databases for both custom and 3rd party applications. 
• Set up, managed, and supported hundreds of client networks and applications.
• Developed web-based applications and dynamic websites.