SB
About
As a results-oriented Machine Learning Engineer with 3 years of experience in computer vision, I've developed a strong track record of designing and deploying robust vision systems for industrial quality control tasks. However, my interests now extend to the rapidly evolving fields of Generative AI and Large Language Models (LLMs), where I can apply my problem-solving skills, data analysis expertise, and passion for innovation to drive impactful projects forward. A strong believer in the power of open-source collaboration, I actively contribute to the machine learning community and am excited about the prospect of joining a team that values innovation, self-learning, and cross-functional collaboration.
Work Experience
2022 - 2025
Machine Learning Engineer
Drove end-to-end machine learning model development, from data acquisition and labeling to model prototyping, training, optimization, and deployment. Championed new tools and methodologies to enhance team collaboration and productivity, working closely with product developers and on-site deployment teams to ensure successful industrial integration.
- Product Feature Development: Designed and deployed core product feature, enhancing robustness and achieving 99.9% accuracy
- Performance Optimization: Optimized deep learning models, boosting inference speed 12x (250ms to 20ms) for industrial deployment
- MLOps & Workflow Automation: Implemented CI/CD pipelines (GitLab CI). Utilized DVC, Ray, and CML for efficient data/model management and experiment tracking
- Data Strategy & Management: Led company-wide data acquisition and labeling initiatives. Guided non-technical staff in labeling 1,400 images in under 2 weeks. Managed 33,000+ images/150,000+ annotations via third-party partnership
- Process Automation: Developed computer vision solution for package compliance, automating 46% of filtering
Python
MLOps
Lightning
Hydra
Ray
ONNX/TensorRT
Gradio
AWS
GitLab CI
Cross-functional Collaboration
Problem Solving & Optimization
Initiative & Ownership
Business Understanding
Communication
April 2019 - July 2019
Research Intern
Under the supervision of Dr. Jordi Cabot, I conducted research on "Discovering Non-Functional Requirements from Published APIs."
- Conducted research on "Discovering Non-Functional Requirements from Published APIs"
- Using a Master-Slave architecture, analyzed non-functional properties of APIs from different locations using Google Cloud Platform
- Published a paper at ICWE2020 conference, which received the Best Demo & Paper Award
Angular
NodeJS
C3.js
Google Cloud Platform
Open Source Contributions
Developed and integrated state-of-the-art keypoint detection and image matching models, significantly expanding the library's capabilities in these domains. These models are currently downloaded over loading... times per month.
Projects
The agent capable of identifying and using the best model among the entire HuggingFace Hub for your Computer Vision needs.
smolagents
Modal
Claude
RAG
Education
Katholieke Universiteit Leuven
2019 - 2023
Master's Degree in Computer Science : Major Artificial Intelligence
Thesis : Data-driven optimisation of substitutions in football
Université de Lille
2018 - 2019
Bachelor's Degree in Computer Science
References
“I am writing to recommend Steven Bucaille for a position that requires strong technical skills, a deep understanding of computer vision, and a collaborative approach. [...] Steven's contributions are technically sound, well-documented, and user-friendly.”
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“His solid knowledge in web technologies and strong programming skills allowed him to design a non-trivial solution that fulfill initial requirements of this project. [...] In summary, I'm confident in stating that he has a strong potential and consider him a valuable candidate for your organization.”
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“... once again, Steven went beyond the objectives I set, he demonstrated a quality that I did not detected before: the ability to deal with the different stakeholders of a project. [...] He then created a surprising and very valuable group dynamics.”
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