About
Hello, and welcome to my portfolio! I am a Data & AI Engineer
with a foundation in Software Engineering and a Master's specialization in Data Science.
My expertise lies at the intersection of complex algorithm design and scalable system architecture.
Having completed my Master’s thesis at
Osaka Metropolitan University (Japan) and graduated with theBest GPA in my Bachelor's, I bring
a disciplined, high-performance approach to every project. Whether it's architecting LLM-driven assistants,
optimizing industrial workflows through Reinforcement Learning, or developing generative 3D AI, I focus on
turning academic excellence into real-world impact. I specialize in bridging the gap between academic
research and production-grade AI. Explore my key projects below, or download my full CV for a detailed
technical breakdown of my experience.
Download my resume.
ML Engineer & Software Engineer
- Birthday: 20 March 1996
- City: Biel/Bienne, Switzerland
- Bachelor: Software Engineering
- Email: alain.gysi@outlook.com
- Nationality: Swiss
- Master: Data Science
Skills
I combine rigorous software engineering principles with advanced machine learning research to build scalable, data-driven solutions. My expertise spans the entire lifecycle of an AI product—from exploratory data analysis and architectural design to cloud deployment and continuous optimization.
Machine Learning
Scikit-Learn, Pandas, Polars, NumPy, SQL •
Advanced Data Visualization
(Matplotlib,
Seaborn) •
Hyperparameter Optimization (Ray Tune, Optuna) •
NLP & Computer Vision
Deep Learning
PyTorch, PyTorch-Lightning, TensorFlow, Keras •
Generative AI & Transformers
(HuggingFace, Nvidia NeMo)
Reinforcement Learning
Ray RLlib, Stable Baselines3 •
Multi-agent System Design •
Unity
ML-Agents
Software Engineering
Docker, Kubernetes, AWS, Linux •
CI/CD Pipelines & Git •
Design Patterns
& Clean Code •
Project Management & Rapid Prototyping
Programming Languages & Frameworks
Python (Expert), C++ (CUDA, Qt), C# (WPF, Unity) •
Java (JEE), Android •
Web (Django, FastAPI) •
LaTeX
Languages
Communication is the backbone of successful engineering. I offer a rare linguistic profile that pairs Native French and Full Professional Proficiency in English with a self-taught JLPT N2 certification in Japanese. This reflects not only my ability to work across international borders but also a relentless drive for self-directed learning and professional growth
Resume
Education
Master thesis
April 2022 - September 2022
Osaka Metropolitan University, Osaka, Japan
Grade: 6.0 / 6.0
Thesis summary:
- Algorithmic Innovation: Engineered a deep learning framework for conditional, frame-by-frame video generation, synthesizing fluid and temporally coherent motion between disjointed anchor frames.
- Dataset Engineering Architected a specialized data pipeline to curate and preprocess high-fidelity motion data from the Demon Slayer anime, creating a custom dataset that enabled the model to learn and replicate complex, non-linear character movements.
- Research Impact: Developed a solution capable of generating plausible in-between frames that closely align with ground-truth physics and movement.
Master of Science in Engineering (MSE) - Data Science
September 2019 - September 2020
HES-SO Master, Lausanne, Switzerland
Grade: GPA 5.5 / 6.0 | Award: Best GPA
Focus: Advanced statistical modeling, deep learning architectures, and large-scale data processing.
Grade TranscriptBachelor of Science in Computer Science - Software Engineering
September 2016 - September 2019
HE-Arc, Neuchâtel, Switzerland
Grade: GPA 5.6 / 6.0 | Award: Best GPA
Thesis summary: Architected an industrial simulation using Unity ML-Agents and Reinforcement Learning to optimize workshop throughput, enabling agents to autonomously adapt to variable order complexity and reduce production latency.
Grade TranscriptProfessional Experience
Data & AI Engineer
September 2025 - Present
Unit8, Lausanne / Zürich, Switzerland
- LLM Orchestration Engineered high-reasoning HR agents using advanced RAG (Retrieval-Augmented Generation) and prompt orchestration, focusing on response grounding and logic consistency.
- Open Source Leadership: Actively contributing to the Darts time-series library, implementing core features and resolving complex architectural issues via peer-reviewed pull requests.
ML Engineer
September 2023 - August 2025
ORamaVR, Geneva, Switzerland
- Text-to-3D generation: Developed an octree-based tokenization system, enabling high-precision text-to-3D generation and transformer-based editing.
- Large-Scale Data Engineering: Designed and implemented a scalable pipeline to process millions of 3D meshes and generate semantic captions, optimizing data workflows for complex generative tasks.
- Semantic Scene Synthesis: Enhanced 3D scene generation capabilities by integrating SBERT/CLIP similarity models and OpenAI APIs for intelligent, context-aware mesh retrieval
- Interoperability & Export: Built seamless .usd export pipelines to ensure high-fidelity asset integration between AI-generated outputs and industry-standard engines like Unity and Blender.
- Cloud Training & Experimentation: Managed multi-model training cycles on Azure and SaturnCloud, utilizing Weights & Biases for rigorous experiment tracking and performance evaluation.
- Advanced ML Implementation: Accelerated R&D cycles by integrating modern frameworks like NeMo and HuggingFace into the core 3D synthesis pipeline, enabling the rapid deployment of novel generative architectures.
Research Engineer in Data Science
September 2020 - Present
Haute Ecole Arc, Neuchâtel, Switzerland
- Full-Lifecycle Development: Led AI projects from initial client requirements and ideation through to deployment of production-ready models.
- Multimodal AI: Developed robust data pipelines for diverse sources, including industrial time-series, computer vision datasets, and natural language.
- Deep Learning Deployment Architected, tuned, and deployed neural networks using PyTorch, TensorFlow, and Ray RLlib, ensuring models met strict performance and latency KPIs.
- Data Engineering: Cleaned and preprocessed data to ensure accuracy, consistency, and develop robust data pipelines to streamline data processing and analysis.
- Collaborative Innovation: Partnered with cross-functional teams to integrate complex ML models into existing enterprise software ecosystems.
Certifications
Hugging Face Deep Reinforcement Learning Course
March 2023
https://huggingface.co/deep-rl-course/
Grade: Excellent
CertificateWinter School in Data Analytics and Machine Learning
Spring 2021
University of Fribourg, Fribourg, Switzerland
Grade: GPA 5.6/6.0
Certificate with gradeProjects
My portfolio represents a convergence of academic research and production-grade engineering. These projects demonstrate my ability to architect complex neural networks, design autonomous systems through Reinforcement Learning, and build robust data pipelines for real-world industrial applications.
Beyond technical research, I am a high-velocity problem solver. A skill I sharpen through international Game Jams, where rapid prototyping and collaborative execution are paramount.
- All
- Deep Learning
- Data Engineering
- Machine Learning
- Reinforcement Learning
- Game Jam
