w.bWALID BAKADIRLet’s talk ↗
COMPUTER VISION · EMBEDDED AI

Intelligence,
outside
the notebook.

I’m Walid, a Computer Vision and Embedded AI Engineer. I build end-to-end AI systems, from data processing and model development to deployment and optimisation, using efficient models designed for low-latency inference on real hardware.

Explore my work ↓View résumé ↗
Eindhoven, Netherlands · Open to opportunities
MEET THE ENGINEEREINDHOVEN / NL
Walid Bakadir
COMPUTER VISION · EMBEDDED AIWalid Bakadir

Connecting models to the physical world.

OPEN TO OPPORTUNITIESTRY THE VISION DEMO ↓
DATA → MODELHARDWARE → VALIDATION
01 / ENGINEERING MINDSET

A model is one part.
The system is the work.

I care about what happens after training: the sensor input, compute limits, timing, controller response, and the evidence that it all works together. My background connects computer vision and signal processing with hands-on embedded engineering.

2+years of professional
AI engineering experience
97%exoskeleton prediction accuracy
under evaluated conditions
MScComputer Vision
& Signal Processing
02 / SELECTED WORK

From data
to working systems.

Real projects. Practical constraints.
Lessons from the complete pipeline.

03 / INTERACTIVE PLAYGROUND

Vision, live in your browser.

Try real YOLO detection.
Then ask a question about Eindhoven.

LIVE MODEL / YOLOv8 NANO

Give the model something to see.

Use your webcam, upload an image, or try my portrait. Images are processed on your device.

ONNX · BROWSER INFERENCE
⌖

Ready when you are.

Choose an input to load the detector.

PRETRAINED MODEL · 80 OBJECT CLASSES
MODEL NOT LOADED
—objects
—inference ms
—processed FPS

First use downloads the model (about 13 MB). Speed varies by device. This is a pretrained YOLO demo, not my custom UAV model.

Model source ↗
Detection labels will appear here.
NATURAL LANGUAGE / REAL CITY DATA

Chat with the map.

Explore Eindhoven, one question at a time.

LOCAL PARSER · LLM NOT CONFIGURED
EINDHOVEN / 116 NEIGHBOURHOODSCBS · 2024
Select a neighbourhood to explore its data.
Share aged 15–24 · low → high
YOUR QUESTION → A TRANSPARENT FILTER

What would you like to know?

    “Young people” means ages 15–24. Rankings use shares, not estimated headcounts. Small or unreported populations are excluded by default.

    Official neighbourhood boundaries and rounded demographic figures, 2024 snapshot. Missing values are excluded. CBS source ↗ PDOK data ↗
    04 / THE JOURNEY

    A foundation in signals.
    A focus on intelligence.

    From automotive embedded systems
    to AI in the physical world.

    01 / EXPERIENCE

    Professional experience

    Industry work and hands-on internships.

    NOV 2024 — PRESENT
    WORK · EINDHOVEN

    Embedded AI Engineer

    VTEC Lasers & Sensors

    Assistive-exoskeleton ML, followed by UAV perception workstream leadership. Data pipelines, real-time deployment, sensor integration and hardware verification.

    APR — OCT 2024
    INTERNSHIP · EINDHOVEN

    Machine Learning Intern

    VTEC Lasers & Sensors

    Initial intention-detection prototypes using IMU and EMG data, preprocessing and feasibility evaluation for embedded inference.

    MAR — JUL 2020
    INTERNSHIP · KENITRA, MOROCCO

    R&D Intern — Embedded Systems

    Ibn Tofail University

    Designed an automated parking prototype with Arduino, weight sensors and position sensors. Developed an OpenCV coin-detection component and 3D mechanical models for prototype validation.

    MAR — JUL 2019
    INTERNSHIP · ERRACHIDIA, MOROCCO

    R&D Intern — Electronics

    Renault–Dacia

    Used OBD-II diagnostics and CAN-bus analysis to investigate vehicle electronic systems. Assisted with sensor calibration, integration and validation.

    02 / EDUCATION

    Education

    The academic foundation behind my engineering work.

    2021 — 2024
    EDUCATION · DIJON, FRANCE

    MSc, Computer Vision & Signal Processing

    University of Burgundy

    A technical foundation connecting image analysis, signal processing and machine learning.

    2020 — 2021
    EDUCATION · DIJON, FRANCE

    BSc, Electronics & Computer Vision

    University of Burgundy

    2018 — 2020
    EDUCATION · KENITRA, MOROCCO

    BSc, Embedded Systems for Automotive

    Ibn Tofail University

    05 / THE TOOLKIT

    The tools behind
    the work.

    Practical experience, grouped by purpose.
    No invented proficiency scores.

    01

    Models & vision

    • Python
    • PyTorch
    • TensorFlow
    • Keras
    • OpenCV
    • YOLO
    • ByteTrack
    • scikit-learn
    • Hugging Face
    • Roboflow
    02

    Embedded & deployment

    • NVIDIA Jetson
    • TensorRT
    • TensorFlow Lite
    • Raspberry Pi
    • Pixhawk
    • MAVLink / PyMAVLink
    • C
    • C++
    03

    Data & software

    • Pandas
    • NumPy
    • MATLAB
    • SQL
    • Matplotlib
    • Power BI
    • Linux
    • Git
    • Docker
    • Flask
    • FastAPI
    BUILDING NEXT

    Deepening my understanding of vision transformers, 3D perception and cloud MLOps. My current expertise is strongest in applied vision and embedded deployment.

    06 / QUICK QUESTIONS

    A little more
    about me.

    Explore answers grounded in my experience.

    CURATED PORTFOLIO Q&A · NO GENERATIVE AI
    Walid on a hiking trip with a group overlooking a forested valley
    BEYOND THE SCREEN

    Hiking, fresh air and good company.

    AI connected to real systems.

    My work connects models with sensors and hardware. At VTEC, I developed real-time UAV detection and tracking on Jetson, and movement-intention inference for an assistive exoskeleton on Raspberry Pi. I take part in the entire loop: data, training, deployment, integration and validation.

    07 / WHAT’S NEXT

    Let’s build
    something that works.↗

    Looking for a Computer Vision, Machine Learning
    or Embedded AI Engineer? Let’s start a conversation.

    Get in touch ↗
    LinkedIn ↗Résumé ↗Walid.bakadir00@gmail.com ↗