Machine Learning Inference Model Development and Deployment

Javier Aquique

Contact for pricing

About this service

Summary

I develop and deploy high-performance machine learning inference models, turning complex data into real-time, actionable predictions. From model optimization to seamless API integration and scalable cloud deployment, I ensure your AI solutions run efficiently and reliably. What sets me apart is my focus on both technical excellence and real-world usability, leveraging my engineering expertise to deliver models that are not just accurate, but also scalable, secure, and ready for production.

What's included

Trained & Optimized ML Model
A fully trained model tailored to your specific use case, optimized for accuracy and performance.
Model Inference AP
A REST or GraphQL API that allows seamless integration of the model into your application or system.
Deployment on Cloud or Edge
Deployment on AWS, GCP, Azure, or on-premises for real-time or batch inference.
Automated Preprocessing Pipeline
A data pipeline that cleans, transforms, and prepares input data before feeding it into the model.
Monitoring & Logging System
A dashboard or logging system to track model performance, latency, and potential drift over time.
Scalability & Performance Optimization
Optimized model inference speed using quantization, model pruning, or hardware acceleration (e.g., GPUs/TPUs).
Security & Access Control
Authentication and authorization mechanisms for secure API access and usage tracking.
Comprehensive Documentation & User Guide
A detailed guide covering API usage, model architecture, deployment setup, and maintenance best practices.
Final Review & Support
A project handoff session and optional post-deployment support for debugging, model retraining, and updates.