Experience
15+ years across AI, aerospace & biotech
AI / ML Engineer · Applied Scientist · R&D Leader
Publications
Refereed papers, technical reports & patent
Projects
Probabilistic ML, NLP, computer vision & more
Education
Penn Engineering, Université Laval, Carleton
Skills
Python, JAX, PyTorch, Pyro, AWS & more
Affiliations
IEEE, AAAI, ACM & more
About
Senior AI / ML Engineer with 15+ years of experience bridging applied research, machine-learning engineering, and cognitive-systems modeling. Expert in probabilistic and variational Bayesian methods, large-scale modeling & simulation, and cognitive-inspired AI architectures. Leads the design of next-generation inference engines and hybrid AI systems integrating symbolic, probabilistic, and neural components. Strong record of technical leadership across biotechnology, aerospace, and simulation industries; published author and patent co-inventor.
Recent Positions
Staff Machine Learning Engineer — VERSES AI
Developed probabilistic ML systems based on variational Bayesian methods for agent-based modeling & simulation. Contributed to hybrid AI architectures inspired by computational neuroscience.
Senior Data Scientist — VectorSolv Corporation
Built Transformer-based LLM pipelines for enterprise document classification, with end-to-end MLOps using Kedro and MLflow on AWS SageMaker.
R&D, AI Engineering — Solid State of Mind
Designed probabilistic ML algorithms for agent guidance, navigation, and control, achieving ~10,000× computation cost reduction versus deep RL baselines.