ML Engineering Lead · Toronto

I build machine learning platforms and the teams that run them.

Currently leading ML platform engineering at Sanofi. My work focuses on infrastructure, MLOps, and the engineering systems that make applied ML reliable at scale.

01 About

I work on the engineering layer that makes ML usable.

I lead machine learning engineering with a focus on platform architecture, MLOps, and production delivery. The throughline in my work is simple: make good models easier to build, ship, and operate.

  • Design for reliability and repeatability from day one.
  • Prefer reusable platform leverage over one-off heroics.
  • Make tradeoffs explicit: cost, speed, complexity, ownership.
  • Build teams and standards that improve over time.

Sanofi · Petco · Loblaw · Numeris · University of Toronto

Python SQL Go Terraform AWS GCP Airflow Vertex AI SageMaker Snowflake CI/CD

02 Work

Selected work

Platform and ML engineering across pharma and retail.

03 Proof

Public artifacts

Implementation checklists, RFC templates, and operational runbooks for ML platform teams. Sanitized but representative of production-grade delivery standards.

Machine-readable: profile.json · experience.json · skills.json

Current build

Agent Soul Kit

A public concept for giving any AI agent a soul file, a memory file, and a more useful operating posture without special backend powers.

Portable files, thin adapters, and a browser playground for tuning warmth, pragmatism, and initiative in public.

Open the kit

04 Contact

Email is best.

I reply fastest to messages about ML platform engineering, MLOps, and engineering leadership. Resume available on request.

Conversations I prioritize

  • ML engineering leadership roles
  • ML platform and MLOps architecture work
  • Production ML delivery and platform modernization
  • Technical advisory conversations with clear scope