StephenSequenzia
AI/ML Engineer & Architect
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Stephen Sequenzia
As a Staff AI/ML Engineer, Architect and Technical Leader I specializing in building production-grade AI/ML systems by combining a deep expertise in ML, software, and data engineering. From designing scalable data pipelines to accelerating GPU training and deploying reliable inference systems, I design, develop and deploy solutions that manage the entire lifecycle of ML models & AI systems.
What I Do
Machine Learning
A Machine Learning Engineer focuses on researching, building and designing self-running Artificial Intelligence systems to automate predictive models. Machine Learning Engineers design and create the AI algorithms capable of learning and making predictions that define machine learning.
MLOps
MLOps is a set of practices, tools, and processes aimed at automating and streamlining the deployment, monitoring, and management of machine learning (ML) models in production environments. MLOps is inspired by DevOps practices but focuses specifically on the unique challenges of deploying machine learning systems. It helps bridge the gap between data scientists, ML engineers, and operations teams to ensure that ML models are reliable, reproducible, and scalable.
Data Engineering
A Data Engineer focuses on preparing data for analytical or operational uses. These engineers are typically responsible for building data pipelines to bring together information from different source systems. They integrate, consolidate and cleanse data and structure it for use in analytics applications. They aim to make data easily accessible and to optimize their organization's big data ecosystem.
Software Engineering
Software engineering is a disciplined approach to designing, developing, testing, and maintaining software systems. It applies engineering principles and methodologies to ensure that software is reliable, efficient, scalable, and meets the needs of users. It involves a combination of programming skills, problem-solving, teamwork, and systematic practices to manage software projects effectively.