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I'm Anthony Chen, a Machine Learning Engineer with 6+ years of experience building production-grade AI systems, LLM-powered copilots, and RAG pipelines. I design intelligent assistants, multi-agent workflows, and scalable backend infrastructure for applied AI products. I own the full lifecycle of ML development—from rapid prototyping and experimentation to deployment, evaluation, and observability. I thrive in secure and regulated environments, work with vector databases, prompt engineering, and cloud-native ML systems using AWS, LangChain/LangGraph, Llama, and TensorRT. I enjoy collaborating with PMs, designers, and engineers to deliver reliable, high-impact AI features that drive measurable user and business outcomes.…I'm Anthony Chen, a Machine Learning Engineer with 6+ years of experience building production-grade AI systems, LLM-powered copilots, and RAG pipelines. I design intelligent assistants, multi-agent workflows, and scalable backend infrastructure for applied AI products. I own the full lifecycle of ML development—from rapid prototyping and experimentation to deployment, evaluation, and observability. I thrive in secure and regulated environments, work with vector databases, prompt engineering, and cloud-native ML systems using AWS, LangChain/LangGraph, Llama, and TensorRT. I enjoy collaborating with PMs, designers, and engineers to deliver reliable, high-impact AI features that drive measurable user and business outcomes.

Anthony Chen

Data Scientist, AI Engineer, AI Developer, +4

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I'm Anthony Chen, a Machine Learning Engineer with 6+ years of experience building production-grade AI systems, LLM-powered copilots, and RAG pipelines. I design intelligent assistants, multi-agent workflows, and scalable backend infrastructure for applied AI products. I own the full lifecycle of ML development—from rapid prototyping and experimentation to deployment, evaluation, and observability. I thrive in secure and regulated environments, work with vector databases, prompt engineering, and cloud-native ML systems using AWS, LangChain/LangGraph, Llama, and TensorRT. I enjoy collaborating with PMs, designers, and engineers to deliver reliable, high-impact AI features that drive measurable user and business outcomes.…I'm Anthony Chen, a Machine Learning Engineer with 6+ years of experience building production-grade AI systems, LLM-powered copilots, and RAG pipelines. I design intelligent assistants, multi-agent workflows, and scalable backend infrastructure for applied AI products. I own the full lifecycle of ML development—from rapid prototyping and experimentation to deployment, evaluation, and observability. I thrive in secure and regulated environments, work with vector databases, prompt engineering, and cloud-native ML systems using AWS, LangChain/LangGraph, Llama, and TensorRT. I enjoy collaborating with PMs, designers, and engineers to deliver reliable, high-impact AI features that drive measurable user and business outcomes.

Available to hire

I’m Anthony Chen, a Machine Learning Engineer with 6+ years of experience building production-grade AI systems, LLM-powered copilots, and RAG pipelines. I design intelligent assistants, multi-agent workflows, and scalable backend infrastructure for applied AI products. I own the full lifecycle of ML development—from rapid prototyping and experimentation to deployment, evaluation, and observability.

I thrive in secure and regulated environments, work with vector databases, prompt engineering, and cloud-native ML systems using AWS, LangChain/LangGraph, Llama, and TensorRT. I enjoy collaborating with PMs, designers, and engineers to deliver reliable, high-impact AI features that drive measurable user and business outcomes.

Skills

Experience Level

Expert

Expert

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Intermediate

Intermediate

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Intermediate

Language

English

Fluent

Work Experience

Machine Learning Research Engineer at Scale AI

July 1, 2023 - November 1, 2025

Built and deployed multiple AI copilots for sales and operations teams using LangChain, LangGraph, MCP, and LlamaIndex, improving workflow automation and increasing active user engagement by 35%. Designed and owned RAG pipelines using ChromaDB and Llama embeddings, including ingestion, chunking, retrieval optimization, and hybrid search, significantly improving answer accuracy and reducing manual lookup time. Contributed to the development and fine-tuning of Defense Llama, a secure LLM built on Meta’s Llama 3 architecture, optimized for defense and national security applications within controlled U.S. government environments. Built scalable backend services and orchestration layers for multi-step agent workflows, improving system reliability, observability, and latency across production deployments. Researched and developed the MVP of video generation model based on SadTalker, optimizing using TensorRT for reduced latency and improved frame rate. Collaborated with cross-functional te

Data Scientist / Machine Learning Engineer at Amazon Web Services

October 1, 2020 - June 1, 2023

Designed and deployed end-to-end machine learning applications on AWS, guiding customer organizations through the full AI/ML lifecycle—from data ingestion and model training to deployment and monitoring. Led cloud architecture design, developing scalable and reusable ML services leveraging SageMaker, Lambda, ECS, and S3. Engineered custom deep learning models for diverse business use cases, improving prediction accuracy and automation efficiency by over 30%. Partnered with cross-functional teams to translate complex business challenges into production-ready ML solutions, accelerating AI adoption across non-technical organizations.

Machine Learning Associate at Amazon Web Services

August 1, 2019 - October 1, 2020

Designed and trained ML models for predictive analytics and NLP, improving accuracy by 25% via hyperparameter tuning and feature engineering. Built and deployed an AI-powered application integrating end-to-end ML pipelines, enabling real-time inference and reducing manual analysis time by 40%. Developed robust data pipelines and automated training workflows using Python, TensorFlow, and AWS, enhancing model retraining efficiency and system scalability. Collaborated with cross-functional teams to deliver production-ready AI systems, contributing to increased deployment reliability and faster model iteration cycles.

NLP/ML Research Intern at SIFT (Smart Information Flow Technology)

January 1, 2019 - August 1, 2019

Developed ML models for DARPA’s MARGARET project to quantify gender bias, combining ethnographic field data with large-scale datasets. Supported TYBALT Phase II SBIR by creating language analysis tools to detect intent to harm U.S. forces using social science frameworks like Moral Disengagement and Integrative Complexity.