John Jorgensen's Resume - AI & Cloud Focus

Summary

Seasoned technical leader with over 30 years of experience in computer and electronics industries, now specializing in cutting-edge AI technologies and cloud operations. Proven track record in building and leading teams to solve complex operational problems, with a deep focus on integrating and optimizing AI tools and workflows in production environments. Extensive knowledge of various LLMs and AI acceleration techniques, coupled with a keen interest in emerging AI research trends.

Technical Skills

AI & Machine Learning:

Large Language Models: Proficient with open-weights models (Mistral, Mixtral, Llama2, Llama3) and proprietary models (Claude family, GPT-3, GPT-4)
AI Frameworks & Tools: OpenAI API, llama.cpp, CrewAI, Microsoft Autogen, OpenInterpreter, Aider, Axolotl (fine-tuning)
AI Acceleration: CUDA, ROCM, model quantization techniques

Cloud & DevOps: AWS, Kubernetes, Docker, Ansible, Puppet, Salt Stack

Programming & Scripting: Python, Shell scripting, Perl

Databases & Message Queues: MySQL, PostgreSQL, RabbitMQ

Monitoring & Performance: Prometheus, Grafana, Thanos

Professional Experience

Technical Operations Manager, Philips (05/2018 to present)
Lead the PAAS operations team, focusing on cloud architecture and AI integration:

Spearhead the adoption and integration of AI tools to boost productivity securely
Manage worldwide Kubernetes installations
Guide customers in migrating to cloud architecture and microservices
Optimize IAAS services for cost-efficiency without compromising quality
Drive long-term technical projects to completion, including AI-related initiatives

Cloud Operations Engineer, Philips (11/2015 to 05/2018)
Focused on cloud infrastructure and big data technologies:

Deployed and managed Hadoop/Spark clusters on AWS using Salt Stack and Ambari
Maintained and upgraded multiple cloud deployments in production
Developed automation tools for efficient deployments and data gathering

AI Research Interests

Actively follow and understand emerging AI research trends, including:

Mixture of Agents: Improving performance by using multiple open source models
BitNet: Exploring trinary logic instead of floats to represent LLMs
Grokking: Investigating training models past overfitting to improve reasoning tasks

Key Projects & Achievements

Led the technical project to achieve and maintain PCI Level 1 compliance
Implemented cloud-config scripts for automated server provisioning in AWS
Co-inventor of patent: "Routing Network Requests Based on a Mobile Signature" (Patent No. 8,526,405)
Contributed to Trac T84 scripting language, including modernization rewrite and new primitives

Education & Certifications