Hi, I'm Justin Michael King

ML/AI Data Operations

Transforming data into intelligent solutions through machine learning and artificial intelligence. Passionate about creating innovative ML models and optimizing data pipelines.

About Me

ML/AI Data Operations & Innovation Enthusiast

As an ML/AI Data Operations specialist, I specialize in developing and deploying machine learning models that solve real-world problems. My expertise spans across data preprocessing, feature engineering, model training, and production deployment.

I'm passionate about leveraging cutting-edge AI technologies to create intelligent systems that drive business value and enhance user experiences. My work involves everything from traditional machine learning to deep learning and neural networks.

0 ML Models Deployed
0 Data Pipelines Built
0 GB Data Processed

Skills & Technologies

My technical expertise in ML/AI and data operations

Machine Learning

Python
TensorFlow/Keras
PyTorch
Scikit-learn

Data Operations

SQL/NoSQL
Apache Spark
Docker/Kubernetes
AWS/GCP

Tools & Frameworks

Jupyter/Pandas
MLflow/Kubeflow
Git/GitLab CI
Tableau/PowerBI

Professional Work History

My career journey in AI/ML, data operations, and technical support

June 2025 - Present Current

AI/ML Data Operations

Apple Inc.

Cupertino, CA
  • Design and implement scalable ML data pipelines for Apple's AI initiatives
  • Optimize data preprocessing workflows for training large-scale machine learning models
  • Monitor and maintain production ML systems ensuring 99.9% uptime
  • Collaborate with cross-functional teams to deploy AI/ML solutions
  • Implement automated data quality checks and validation frameworks
  • Manage petabyte-scale datasets across distributed computing environments
February 2025 - May 2025

Data Collection Moderator

Apple Inc.

Cupertino, CA
  • Reviewed and validated training data for machine learning model development
  • Ensured data quality standards and compliance with privacy regulations
  • Coordinated data collection processes across multiple product teams
  • Implemented data annotation guidelines and quality control measures
  • Collaborated with data science teams to improve dataset accuracy
  • Managed data labeling workflows and vendor relationships
March 2020 - April 2024

Quality Control, Remote Desktop Support & Materials Handler

Transpere

San Diego, CA
Quality Control:
  • Implemented quality assurance protocols reducing defect rates by 25%
  • Conducted statistical analysis of production data to identify trends
  • Developed automated testing procedures and quality metrics dashboards
  • Coordinated cross-department quality improvement initiatives
Remote Desktop Support:
  • Provided technical support for 200+ remote employees across multiple time zones
  • Troubleshot software and hardware issues reducing resolution time by 40%
  • Maintained remote access systems and security protocols
  • Created technical documentation and user training materials
Materials Handler:
  • Managed inventory systems and optimized supply chain processes
  • Implemented barcode scanning systems improving accuracy by 30%
  • Coordinated shipping and receiving operations
  • Maintained detailed records using ERP systems and databases
June 2016 - August 2019

Logistics Coordinator

Amazon

San Diego, CA
  • Coordinated delivery routes and schedules for 50+ drivers daily
  • Optimized logistics operations resulting in 15% improvement in delivery times
  • Managed warehouse operations and inventory tracking systems
  • Analyzed delivery data to identify bottlenecks and process improvements
  • Trained new team members on logistics software and safety protocols
  • Maintained communication with customers regarding delivery status
  • Utilized Amazon's proprietary logistics systems and data analytics tools

Featured Projects

Showcasing my latest work in ML/AI and data science

Recycling Center App

Flutter-based recycling center management system with ML-powered waste classification and route optimization algorithms.

Flutter Python TensorFlow Computer Vision

ML Data Pipeline

Automated ETL pipeline with real-time data processing and model retraining capabilities for production ML systems.

Python Apache Spark Docker AWS

Predictive Analytics Dashboard

Interactive dashboard for real-time predictive analytics with advanced visualization and anomaly detection capabilities.

Python Streamlit Plotly PostgreSQL