README.md
Pierre Blachere
AI engineer in Singapore, taking AI products from prototype to production across models, backend systems, and interfaces.
Looking for AI/ML engineering roles where I can keep owning a product end to end, not just the model layer.
About
I am most interested in the point where an ML or AI system becomes a product someone can use and trust. At Hutchinson, I have taken document intelligence and RAG systems from proof of concept to production on Azure. My own projects continue that end-to-end approach across Python services, data pipelines, web interfaces, and mobile apps.
Why I build
A lot of my projects start with a simple question: why not build it myself? AI assisted development makes it easy to create small, personal tools shaped around the way I actually live and work. They do not all need to become companies. Sometimes I want an app without ads, subscriptions, or ten features I will never use. Sometimes I just want to find out whether an idea works or not.
Stack across projects
- TypeScript 60%
- Python 33%
- Rust 7%
Skills
- Programming languages
- Python · TypeScript · C++ · SQL · Bash
- Web & frontend
- React · Next.js · TypeScript · HTML/CSS
- Backend & APIs
- FastAPI · REST APIs · SQLAlchemy · Pydantic · Microservices architecture
- AI/ML frameworks
- PyTorch · Hugging Face Transformers · LangChain · LangGraph · Azure OpenAI · Google GenAI SDK · LoRA/PEFT · Scikit-learn · Pandas · NumPy · OpenCV
- LLM & GenAI
- RAG pipelines · Multi-agent orchestration · MCP · Vector search & embeddings · Prompt engineering · Structured output extraction · Ragas · Langfuse · OpenTelemetry
- Databases
- PostgreSQL · pgvector · Neo4j
- Cloud & DevOps
- Azure · Docker · Kubernetes · GitHub Actions CI/CD · Terraform · Agile/Scrum
- Developer tools
- Git · Linux · ROS
- Human languages
- English (fluent) · French (native) · Spanish (fluent) · Chinese (intermediate, HSK4)
Start here
Download résumé