Jorge Sáez Gómez

Senior AI/ML engineer & architect Available for assignments

I turn messy real-world signal into ML that runs in production.

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.

Building AI
10+ yrs
Disclosed funding raised
€15M+
Team grown from
1→40+
Devices in the field
10,000s

Three ways teams bring me in

A

Production ML & CV architecture

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.

  • Edge & embedded
  • MLOps
  • Computer vision
B

PoC → production

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.

  • Pipelines
  • Evaluation
  • Reliability
C

LLM & VLM systems

Structured, traceable LLM and vision-language pipelines — matching, extraction, and evaluation that stay explainable and keep per-call cost under control.

  • LLM pipelines
  • VLMs
  • Cost & latency

Remote, part-time, invoiced through my consultancy. Most engagements run as a monthly retainer.

Signal in, systems out

Founding member & Director of Data Science Connecterra 2014 – 2023

Wearable AI for dairy farming, from first prototype to scale-up

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

Strategic data scientist (contract) Datamars 2023 – 2026

Transformer-based anomaly detection for time-series

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

External consultant Taidy 2024 – 2025

Applied computer vision on thermal imagery

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

Co-founder & CTO NoSocial 2025 – 2026

Privacy-first LLM matching

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.

Press & recognition

  • EL PAÍS 2017 · ES

    Interviewed on wearable sensors for dairy cattle.

  • Interviewed on turning raw sensor data into decisions farmers act on.

  • Web Summit 2015

    Connecterra won the Alpha PITCH category — 200 finalists from 2,100+ applicants. Reported by StartupJuncture.

  • GizTab ES

    Quoted on smart collars for dairy herds.

A few markers

  • Research Co-author, peer-reviewed conference paper on quantifying dairy-cow behaviour with multi-stage SVMs (ECPLF 2017, with Aarhus University).
  • Graduate study M.Sc. in Artificial Intelligence at the University of Amsterdam, supervised by Max Welling.
  • Languages Spanish (native), English (C1–C2), Dutch (B1–B2), Indonesian (A1–A2).

What I build with

ML & modelling

  • PyTorch
  • TensorFlow
  • PyMC
  • Computer vision
  • LLMs / VLMs
  • Time-series

Systems & infra

  • Linux
  • Kubernetes
  • Docker
  • Azure
  • AWS
  • Kafka

Data

  • PostgreSQL
  • MongoDB
  • Event Hub

Languages & tools

  • Python
  • C / C++
  • React
  • Reflex
  • uv