Nick Nguyen
@nicknguyen
Senior AI/ML engineer specializing in LLMs, RAG systems, and production MLOps.
What I'm looking for
I am a Senior AI/ML Engineer with over 8 years delivering end-to-end NLP, computer vision, and machine learning solutions across healthcare, financial, and e-commerce domains.
I combine deep ML research with enterprise-grade MLOps, owning model design through scalable production deployment, monitoring, and optimization using tools like PyTorch, Hugging Face, LangChain, Azure ML, and AWS SageMaker.
My recent work includes architecting an enterprise RAG platform, fine-tuning Llama-3 and Mistral models with LoRA and DeepSpeed to cut inference costs, and building multi-agent orchestration and high-throughput retrieval pipelines that serve hundreds of thousands of queries daily.
I continuously improve operational reliability and observability—implementing CI/CD, canary rollouts, and monitoring stacks (W&B, Prometheus, Grafana)—and I seek roles where I can apply scalable LLM systems and MLOps best practices to drive measurable product impact.
Experience
Work history, roles, and key accomplishments
Senior AI/ML Engineer
Stepwise
Feb 2024 - Present (1 year 11 months)
Architected and delivered an enterprise RAG platform for healthcare and financial clients, fine-tuned Llama-3 and Mistral-7B to improve domain reasoning and reduced inference costs by 35%, and built multi-agent orchestration handling 200K+ daily queries.
Developed BERT-based ranking models and hybrid semantic retrieval for search relevance on Azure ML, built scalable feature pipelines integrating clickstream and embeddings, and automated retraining and deployment with continuous monitoring.
Machine Learning Engineer
7 Sensing Software
Sep 2018 - Oct 2021 (3 years 1 month)
Designed and deployed Airflow data pipelines and real-time image classification/OCR modules for edge devices, engineered device-to-cloud telemetry and managed edge model deployment with monitoring.
Delivered OCR-based identity verification pipelines, video compression and real-time scoring systems, and embedded acoustic detection prototypes, reducing manual processing and enabling real-time inference on edge devices.
Designed and optimized ETL pipelines with Python and Spark, managed Redshift and S3 data warehouses, and automated data workflows with Airflow to improve analytics reliability and reduce missing values.
Software Engineer
Vega IT
Oct 2015 - Jan 2017 (1 year 3 months)
Built baseline ML models and refactored prototypes into maintainable code with tests and automation to support analytics and product experiments.
Education
Degrees, certifications, and relevant coursework
University of Leeds
Master of Science, Computer Science
Completed a Master of Science in Computer Science with advanced study in machine learning and related research topics.
University of Glasgow
Bachelor of Science, Computer Science
Completed a Bachelor of Science in Computer Science covering foundational topics in programming, algorithms, and systems.
Tech stack
Software and tools used professionally
Azure Synapse
Apache Spark
AWS Glue
Azure Bot Service
GitHub
GitLab
Kubernetes
Docker Compose
Azure Kubernetes Service
GitHub Actions
GitLab CI
DB
PostgreSQL
Rollout
OpenCV
Redis
Azure DevOps
JavaScript
Java
Azure Machine Learning
TensorFlow
PyTorch
MLflow
scikit-learn
DeepSpeed
FastAPI
Grafana
Prometheus
Azure Monitor
Elasticsearch
Algolia
Azure Cognitive Search
Azure Functions
Airflow
Time Analytics
SQL
Azure Cosmos DB
Azure Blob Storage
XGBoost
Hugging Face
LangChain
Weights & Biases
CrewAI
Azure Logic Apps
Cosmos
Bash
Enhance
Faiss
Orb
PEFT
Availability
Location
Authorized to work in
Job categories
Skills
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