James B.

Key Skills

Software

SuperAnnotate

Snorkel AI

Remotasks

Mercor

Micro1

Mindrift

Scale AI

Top Subject Matter

AI/ML model production for recommendations and healthcare-related automation

AI/ML model deployment for finance analytics (portfolio optimization, fraud detection)

Legal Services & Contract Review

Top Data Types

Text

Document

Image

Top Task Types

Fine-tuning

Prompt + Response Writing (SFT)

Computer Programming/Coding

Evaluation/Rating

Freelancer Overview

Senior Full Stack Developer / AI Engineer / Team Lead, Membersy (end-to-end AI-powered applications). Brings 13+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science, Harrison College (2009). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Fine-tuning.

Labeling Experience

Senior Full Stack Developer / AI Engineer / Team Lead, Membersy (end-to-end AI-powered applications)

Fine-tuning

Led end-to-end productionization of machine learning models by collaborating with data science teams, focusing on improving model performance for real-time recommendations and automation. Built ETL pipelines to preprocess and clean multi-source datasets so trained models could consume high-quality inputs. Implemented deployment and operational workflows to support ongoing inference, monitoring, and continuous improvement in production systems. • Productionized models using TensorFlow and PyTorch • Engineered ETL pipelines with Kafka and Spark for dataset readiness • Integrated model inference into backend APIs and front-end interfaces • Decreased inference latency and improved uptime through CI/CD and Kubernetes orchestration

2020 - Present

Full Stack AI Developer, Envested (AI-powered investment management tools)

Fine-tuning

Developed and deployed AI-powered investment management models by working closely with data science teams to optimize portfolio optimization, fraud detection, and personalized advisory services. Built data pipelines to process large volumes of transaction data and prepare inputs for model training and inference. Containerized and orchestrated AI microservices to enable reliable, near real-time analytics in production. • Deployed and optimized machine learning models for decision-support tasks • Engineered Kafka-based pipelines with SQL (PostgreSQL) and NoSQL (MongoDB) • Reduced data latency and improved model accuracy metrics • Implemented RESTful APIs integrating AI models into application workflows

2015 - 2020

Education

Work History