How I can help
I’m interested in work that values depth, clear thinking, and well-engineered systems. Typically this looks like focused projects or senior individual contributor roles.
Machine learning engineering
End-to-end models: data prep, feature design, training, evaluation, and deployment. Pragmatic about trade-offs and baselines.
- • Supervised & unsupervised ML
- • Ensemble models & interpretability
- • API-based serving
Reinforcement learning & optimisation
Framing problems as decision processes when that actually helps: routing, control, and experimentation with RL vs simpler baselines.
- • Custom environments & agents
- • Simulation-to-real workflows
- • Comparisons vs OR / heuristics
Data engineering & MLOps
Pipelines and infrastructure for ML systems that are meant to survive longer than a demo.
- • ETL/ELT, dbt, SQL, Snowflake
- • FastAPI, Docker, CI/CD
- • Cloud ML (e.g. Vertex AI)
A small note
I’m careful about taking on work where ML is the wrong answer. Sometimes a simpler analytical or engineering solution is better, and I’m happy to say that out loud.
If you have something in mind, get in touch and we can figure out whether it’s a good fit.