Christopher M.

Key Skills

Software

Scale AI

Other

AWS SageMaker

Top Subject Matter

LLM/RAG and customer-service NLP for engagement and support automation

Model training refinement and evaluation for regulatory NLP/vision systems

Computer vision and document/NLP modeling with segmentation for security and anomaly detection

Top Data Types

Document

Image

Text

Top Task Types

Text Generation

Segmentation

Object Detection

Freelancer Overview

Senior Machine Learning Engineer | Lead Engineer at Scale AI. Brings 14+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI, Other, and AWS SageMaker. Education includes Bachelor of Computer Science, University of Pittsburgh (2012). AI-training focus includes data types such as Document, Computer Code, and Programming and labeling workflows including Text Generation, Evaluation, and Rating.

Labeling Experience

Senior Machine Learning Engineer | Lead Engineer at Scale AI

Scale AIDocumentText Generation

Developed and deployed large-scale AI solutions using LLMs with LangChain and RAG technologies, implying AI training/evaluation data preparation for generative workflows. Built supporting ingestion and processing pipelines for real-time applications that depend on labeled or curated text corpora. Enabled user engagement improvements via an AI chatbot integrated into backend services. • Implemented an AI-powered chatbot for customer service using Spring Boot and Java microservices. • Delivered scalable AI solutions in SaaS environments with end-to-end data pipelines. • Authored and deployed ML applications via Django REST Framework and AWS container services. • Collaborated on real-time data processing pipelines using Kafka, Spark, and PyTorch.

2023 - 2026

Senior Machine Learning Engineer at Kiwitech

Other

Built and refined AI models for NLP and computer vision tasks, which would require training/evaluation datasets and careful model assessment. Designed real-time pipelines for object detection and anomaly detection, supporting iterative experimentation and performance validation. Led monitoring and retraining to maintain model accuracy and consistency across dynamic environments. • Refined large language models to improve accuracy for AI-driven regulatory systems. • Engineered real-time object detection and image segmentation solutions using TensorFlow and PyTorch. • Redesigned an anomaly detection pipeline with automated hyperparameter tuning for time-series models. • Implemented continuous monitoring and retraining to achieve high predictive analytics consistency.

2020 - 2022

Machine Learning Engineer at Edlution PteLtd

AWS SageMakerSegmentation

Developed and evaluated deep learning models for real-time object detection and image analysis, implying creation/curation of labeled datasets for training. Implemented a Bayesian segmentation network for anomaly detection and risk assessment, requiring segmentation-oriented labels. Prototyped and evaluated SOTA deep learning models for machine learning and computer vision tasks. • Deployed a serverless CV+NLP platform on AWS for document parsing. • Implemented a Bayesian Segmentation Network for anomaly detection and risk assessment with reported annual savings. • Researched and evaluated SOTA deep learning models and rapid software prototypes for CV/ML. • Applied deep learning models for real-time detection and reduced false positives significantly.

2015 - 2019

Machine Learning Engineer at Utrip

OtherObject Detection

Built recommendation and NLP-based systems and developed real-time object detection models, which would depend on labeled datasets for training and evaluation. Engineered and deployed vision models using YOLOv8 and supporting components for video stream detection and tracking. Improved predictive performance via clustering and topic/keyword extraction approaches. • Developed a recommendation engine analyzing CRM and social media data. • Enhanced product recommendation accuracy using NLP combined with K-means clustering. • Engineered real-time object detection models using YOLOv8, OpenCV, and backend APIs. • Pioneered real-time computer vision algorithms for object detection and tracking in video streams.

2013 - 2015

Education

Work History