Cristian Samson

Hi, I'm @CrSamson,

Applied AI Engineer

Selected work

Projects across AI agents, ML, and specialized AI.

AI Agents

02

Machine Learning

02
FTR Prophet preview

FTR Prophet

Walk-forward ML for energy market trading.

  • Walk-forward validation with anti-leak guards
  • 36-feature LightGBM ensemble
  • $5.3M simulated net profit
PythonLightGBMpandasscikit-learn

Specialized AI

02
Splendor.ai preview

Splendor.ai

Neural networks that learned to play Splendor.

  • ISMCTS expert data generation
  • Imitation-learning neural networks
  • 100K+ state-action training pairs
PyTorchNumPyGame AI

ML Fundamentals

02
About

Industrial engineering background. Applied AI on production systems.

Cristian Samson

Currently

  • Shipping RAG and LLM-evaluation systems in production
  • Finishing my M.Sc. in Data Science at HEC Montréal (2026)
  • Open to discussing applied AI roles, freelance work, and interesting collaborations

Applied AI Engineer based in Montréal. I build production-grade machine learning and generative AI systems in an enterprise context, focused on the work that has to run after the demo ends. My background sits at the intersection of industrial engineering and data science, picked up at Polytechnique Montréal and HEC Montréal.

What I do today

Currently working on RAG pipelines, automated LLM-as-a-Judge evaluation frameworks, and performance monitoring systems for multiclass ML models in production. Before this, two years of RPA automation work taught me how to design systems that run reliably without supervision.

Outside of work

I build AI side projects across a few categories: agentic systems (StaffBot, Brevio AI), trading models (an HEC Data Challenge entry that generated $5.3M in simulated net profit), and specialized tools (PharmaOCR, Splendor.ai).

I co-founded the Polytechnique Business Case Center during my undergrad. Turning ambiguous business problems into structured analyses is most of the actual job.

From IE to applied AI

Industrial engineering taught me to look at systems end to end: flows, bottlenecks, what creates value and what just creates motion. Applied AI is the same lens with sharper tools. When a model takes hours of grinding work off someone's plate, the win is human, not technical.

Stack

08

Programming

PythonSQLRJava

Python Stack

scikit-learnPySparkpandasNumPySciPyLangChain

Machine Learning

RegressionClassificationClusteringXGBoostRandom ForestsLightGBM

Deep Learning

PyTorchTensorFlow

Generative AI

LLMsRAGPrompt EngineeringLangChainOpenAI APILLM-as-a-Judge

Cloud & Big Data

Azure MLMicrosoft Azure

MLOps

GitMLflowCI/CDDocker

Languages

EnglishFrench

Education

02
  • M.Sc. in Data Science

    HEC Montréal

    2024 to 2026

  • B.Eng. in Industrial Engineering

    Polytechnique Montréal

    Co-founder, Polytechnique Business Case Center

    2018 to 2022