David Rose
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Staff ML Engineer | Generative AI, Agent Systems, LLM Fine-Tuning, Production AI Platforms
Staff Machine Learning Engineer with 10+ years building production AI/ML systems, from real-time recommender systems to modern generative AI platforms. My recent work has focused on agent systems, LLM fine-tuning, distributed execution patterns, and production AI infrastructure. At Zeta Global, I’ve led cross-functional work spanning multi-agent product architecture, long-running AI workflows, multimodal model fine-tuning, and the platform patterns needed to deploy and operate AI systems reliably. Across roles, I’ve worked on real-time inference, recommender systems, NLP, reinforcement learning, RAG, tool-using LLM systems, and production deployment workflows. I’m especially interested in building AI systems that move beyond demos into durable products teams can actually use. Core areas: generative AI, agent systems, LLM fine-tuning, model evaluation, RAG, tool use, AI platform architecture, Kubernetes, AWS, observability, and real-time ML systems. I build things that ship. GitHub: https://github.com/cipher982
Udacity
Deep Reinforcement Learning
January 1, 2018 – January 1, 2019
Udacity
Self Driving Cars, Autonomous Vehicles
January 1, 2017 – January 1, 2018
Udacity
Machine Learning
January 1, 2015 – January 1, 2016
Samford University
Economics & Finance
January 1, 2008 – January 1, 2013
Zeta Global
Staff Machine Learning Engineer
April 1, 2025 – Present
New York, New York, United States
Zeta Global
Lead Machine Learning Engineer
April 1, 2023 – April 1, 2025
New York, New York, United States
Zeta Global
Senior Machine Learning Engineer
November 1, 2019 – April 1, 2023
New York, New York, United States
IgnitionOne (acquired by Zeta Global)
Senior Data Scientist
April 1, 2019 – November 1, 2019
Greater Atlanta Area
StrategyWise
Data Scientist
August 1, 2016 – April 1, 2019
Greater Atlanta Area
Regions Financial Corporation
Software Engineer
July 1, 2015 – June 1, 2016
Birmingham, Alabama Area
Management Solutions
Data Analyst
October 1, 2013 – June 1, 2015
Birmingham, Alabama Area
Bulldog Investment Fund
Technology Sector Manager
November 1, 2012 – May 1, 2013
Birmingham, AL
Samford University
Technology Services
August 1, 2008 – June 1, 2011
Cumberland Law School and Samford Library
Practical Machine Learning
Coursera
June 24, 2026 – Present
R Programming
Coursera
June 24, 2026 – Present
Building Deep Learning Applications with Keras 2.0
June 24, 2026 – Present
Inferential Statistics
Coursera
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Exploratory Data Analysis
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong commitment to the data science and machine learning domain, with continuous learning through Udacity nanodegrees and Coursera certifications. Their experience spans from Data Analyst to Staff Machine Learning Engineer, demonstrating versatility and a broad understanding of data-driven roles. The transition from a Data Analyst role early in their career to advanced ML engineering, and then back to a target role of Data Analyst, suggests a potential interest in leveraging their deep ML knowledge for advanced analytical tasks. The diverse project experience, from political campaigns to financial reporting and advertising, indicates adaptability to various business contexts.
Soft Skills & Operational Fit
The candidate's experience in leading teams, driving architectural decisions, and partnering with diverse stakeholders (engineers, designers, data scientists) suggests strong leadership, collaboration, and communication skills. Their progression through various roles at Zeta Global indicates adaptability and growth within an organization. The descriptions highlight a focus on turning research into production capabilities, indicating a practical, results-oriented approach.