A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
Cybersecurity Solutions Architect/Engineer (Databricks, AI/ML) Triangle Cyber, LLC Morrisville, NC Job Details 21 hours ago Qualifications AI models Cybersecurity threat analysis Databricks Azure Computer vision R AI platforms (beyond public GPTs) Managing data teams Tableau IT strategy formulation (System development task) Data governance Security data analysis System design for system development Technical solutions implementation Programming languages Machine learning cloud services AWS Machine intelligence Product development Managing teams of scientists Technology management Model deployment Customer engagement Developing large-scale AI models Project delivery management Cloud solution engineering Threat intelligence AI strategy Fraud Detection Systems Project stakeholder communication Full Job Description Triangle Cyber is seeking a Cybersecurity Solutions Architect/Engineer for a U.S. federal client. The ideal candidate will have significant experience with Databricks and developing expert-level AI/ML analytic solutions that analyze very large volumes of data from disparate sources to detect cybersecurity threats and fraud schemes.
NOTE:
This position will close at 5 p.m. on Wednesday, September 9, 2026 Required Must be a U.S. Citizen and reside in the United States, including Alaska and Hawaii. Must hold a Bachelor of Science degree (minimum) in a relevant technical field of study (Computer Science, Engineering, etc.). Must have a minimum of eight (8) years of relevant experience, including Databricks, AI/ML, and data analytics. Must be an expert in data science and AI/ML concepts used for fraud detection Must have deep expertise in AI/ML solution development, data science, data strategy and governance, and customer and stakeholder engagement, along with hands‑on experience designing AI‑powered solutions that integrate large language models, computer vision, and advanced analytics within secure, high‑performance environments Must be able to direct specialized teams comprising data scientists, data engineers, and business intelligence specialists driving key AI and advanced technology solutions across secure environments Must be able to manage delivery across multiple engagements including business intelligence, technology and tradecraft, financial operations, workforce analytics, cyber, artificial intelligence, risk management, and product development to enhance organizational performance (Python, SQL, Tableau, AWS) Must have advanced skills applying AI/ML tools to accelerate business activities, including but not limited to programming and script development Must have expert-level knowledge of: AI/ML Solution Architecture Data Science and Advanced Analytics Technology Strategy and Implementation Data Strategy and Governance MLOps and Model Lifecycle Management Azure Databricks Python, SQL, R Development
