Senior AI/ML engineer & architect Available for assignments
Ten years building AI end-to-end — wearable sensors and edge inference, cloud ML pipelines, computer vision, and LLM systems. I ship the whole path, from the noisy input to the model serving at scale.
01 / What I take on
Design and build AI end-to-end — from edge devices and sensors through to cloud training, serving, and monitoring. The full path, built to actually hold up in the field.
Take a model that works in a notebook and turn it into a reliable system: pipelines, evaluation, infrastructure, and the unglamorous engineering that makes it dependable at scale.
Structured, traceable LLM and vision-language pipelines — matching, extraction, and evaluation that stay explainable and keep per-call cost under control.
Remote, part-time, invoiced through my consultancy. Most engagements run as a monthly retainer.
02 / Selected work
One of four founders and the first employee. Designed the original neural networks that classify low-level cow behaviour from wearable sensors, wrote parts of the embedded Linux base-station stack bridging farm to cloud, ran field deployments by hand, then moved into directing a data-science team of five and the cloud ML pipelines behind it all.
accelerometer streamsbehaviour classification on 10,000s of devices
After Datamars acquired Connecterra, I kept leading experimental projects part-time: data exploration, stakeholder alignment, and a novel transformer architecture for outlier detection in time-series sensor data.
noisy time-seriesflagged anomalies
Built a web app that compares left/right body temperatures to flag potential injuries, deployed visual-understanding models (LLaVA, Qwen-VL, Grounding DINO, DensePose), and trained a custom convolutional model from scratch that outputs 2-D probability heat-maps to place regions of interest on thermal images.
thermal imagesROI heat-maps & injury flags
Built LLM pipelines that produce structured, traceable, explainable evaluations of candidates and roles — the engineering challenge being to keep evaluations deep enough to be useful while keeping per-match cost low enough to scale.
unstructured profilesexplainable matches
The same lens runs in reverse: assessing someone else’s technical design rather than building my own. Happy to support due diligence — investor or acquirer side, or a second opinion before you commit to a build.
03 / Press
Interviewed on wearable sensors for dairy cattle.
Interviewed on turning raw sensor data into decisions farmers act on.
Connecterra won the Alpha PITCH category — 200 finalists from 2,100+ applicants. Reported by StartupJuncture.
Quoted on smart collars for dairy herds.
04 / Background
05 / Stack
ML & modelling
Systems & infra
Data
Languages & tools
Fun
I'm a Rescue Diver with over 150 dives and I have participated in coral reef restoration programs in Thailand and Malaysia.
This tab is a work in progress; the bottleneck is me not enjoying taking pictures of myself.
Blog post · 2026
This is a placeholder post to prove out the routing and layout for individual
writing under /thoughts. Real content goes here once it exists.
Each post lives at its own URL, like this one at /thoughts/demo-post,
so it can be linked and indexed on its own rather than living behind a tab click.
