I build AI people actually use

I build AI for hospitals and for big tech. Parkinson's detection in production at Amplifier Health, smart-home features at Huawei, federated learning across ten institutions at the Jewish General Hospital. I also built an AI product on my own and sold it.

00 · Start here

Ideas are cheap. Working software isn't.

I'm Reza Amini Gougeh. I take AI ideas and turn them into things people actually use: a voice assistant a patient can talk to, a pipeline that catches Parkinson's in a recording, a search engine that cites its sources instead of making them up.

Most of my work has been in health. Hospitals in Montréal and Ottawa, a research consortium spanning ten institutions, a medical AI company. I've also spent a year at Huawei building smart-home features, and a stretch running my own company until I sold it.

I move between fields on purpose. Health, consumer hardware, and more recently legal tech and large document corpora. Every niche breaks your assumptions in a different way, and you only learn the new thing by being somewhere unfamiliar. The tools carry over. The instincts have to be rebuilt each time.

I care about the boring parts too. Data that's clean, models you can explain, systems that stay up. That's usually where a good demo turns into a real product.

Reza Amini Gougeh

Reza Amini Gougeh

Montréal, QC

Now

Founder, building something new in legal tech

Shipped at
HuaweiJewish General HospitalAmplifier HealthJuztina
Also

One startup, built and sold

Speaks

Azerbaijani, Persian, English, French

More about me

01 · Work

Where I've built things

Seven roles, mostly in health AI and applied research. The common thread is getting models out of notebooks and into production.

  1. Feb 2026 – Present

    Founder

    Building something new in legal tech, Montréal / Remote

    • Early-stage work on an AI product for legal teams. Too soon to say much publicly.
    • Same pattern as last time: build the thing, put it in front of people, keep what works.
  2. Dec 2025 – Present

    AI Lead

    Juztina LLC, Remote

    • Built the AI pipelines and data infrastructure behind the platform, and tuned LLM performance in production.
    • The AI features cut churn by 10% and lifted feature adoption by 25%. Deployed on Azure and AWS EC2.
  3. Oct 2025 – Feb 2026

    Founder & Applied AI Engineer

    Stealth AI Startup, Montréal / Remote

    • Shipped a full-stack AI product on my own: web platform, voice AI, audio features, plus RAG pipelines and a citation engine over a large document corpus.
    • Made every technical call, then sold the company and the technology behind it.
  4. Feb 2025 – Oct 2025

    AI Engineer

    Amplifier Health, Remote

    • Built the data pipelines and AI infrastructure, and put deep learning models into production for medical use, including Parkinson's detection.
    • Ran the stack on GCP Cloud Run and AWS EC2.
  5. 2024 – 2025

    Lead Machine Learning Engineer

    CIUSSS West-Central Montreal / Jewish General Hospital, Montréal, QC

    • Led the AI work for precision medicine in the mental health department at the Lady Davis Institute.
    • Took models from research question to something clinicians could actually use.
  6. 2023 – 2024

    HCI Research Engineer

    Huawei Technologies, Markham, ON

    • Built AI and IoT features for phones, homes, and cars, and cut system latency by 20%.
    • Prototyped ideas, demoed them, and contributed to patents.
  7. Feb 2023 – Apr 2023

    Full-Stack Developer & AI Specialist

    UQO / Élisabeth Bruyère Hospital, Ottawa, ON

    • Built a virtual companion for patients in Unity, running on the ChatGPT API.
    • Improved speech recognition and text-to-speech, and engagement went up 55%.
  8. 2021 – 2023

    Machine Learning Engineer

    CIUSSS West-Central Montreal / Jewish General Hospital, Montréal, QC

    • Worked on DREAM BIG, a consortium of 10+ institutions studying how genes, prenatal adversity, and early childhood environment shape children's wellbeing.
    • Built federated-learning decision support systems and hardened the models to keep sensitive data safe.

02 · Projects

A few I'm proud of

Some were research, some were weekend builds, some turned into products. All of them ran.

04 · Publications

Peer-reviewed work

Four that matter, in plain language. The rest are on Scholar.

  1. Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management

    Sensors · 2024

    What the wearables field has actually managed to measure about people, and where the claims outrun the evidence.

  2. Optimizing Auditory Immersion Safety on Edge Devices: An On-Device Sound Event Detection System

    Odyssey · 2024

    VR headsets cut you off from the room. This runs sound-event detection on the headset itself, so it can warn you without sending any audio away.

  3. Multisensory Immersive Experiences: A Pilot Study on Subjective and Instrumental Human Influential Factors Assessment

    QoMEX · 2022

    We added smell, wind and touch to VR and measured whether people actually felt more present, instead of asking them afterwards.

  4. Towards instrumental quality assessment of multisensory immersive experiences using a biosensor-equipped head-mounted display

    Quality and User Experience · 2023

    Putting biosensors in the headset so the quality of an experience can be measured while it happens.

05 · Skills

What I'd vouch for

Graded by what I'd be comfortable owning in production, not by a percentage. Each line links to where it ran.

I'd own this in production

Shipped to production and I have debugged them under pressure.

Solid, give me a day to warm back up

Built real things with these, just not this month.

Machine learning
Python, PyTorch, TensorFlow, scikit-learn, pandas, NumPy, SHAP, LIME
LLMs and RAG
RAG design, LangChain, LangGraph, LangSmith, OpenAI, Gemini, Claude, Retell.ai voice AI
Data and storage
PostgreSQL, Supabase, Milvus, Qdrant, pgvector
Shipping and ops
Docker, Kubernetes, GCP, AWS, Azure, CI, MLflow, DVC, Weights & Biases
Product surface
FastAPI, Flask, Django, Streamlit, Stripe, Unity

06 · Contact

Say hello

If you're building something in AI and want another pair of hands on it, or you just want to talk about a problem, reach out on LinkedIn or GitHub. I answer.