Michael Tunwashe
I’m Michael, a Math B.Sc. graduate who’s focused on building reliable AI systems and infrastructure—especially around LLM evaluation, RAG, and trustworthy deployment.
About
I’m Michael, a Math B.Sc. graduate who’s focused on building reliable AI systems and infrastructure—especially around LLM evaluation, RAG, and trustworthy deployment. I enjoy turning probabilistic thinking into practical engineering, and I like making AI outputs measurable through evaluation rubrics and structured workflows.
I’ve worked on production-style AI and data projects, from designing and automating pipelines with Python/FastAPI/SQL to building dashboards and improving data quality. I’m also passionate about trustworthy AI practices, including integrity-focused tooling for real auditing use cases, and I keep strengthening my foundation in Linux and distributed systems to ship dependable applications.
- 2 years' experience
- Joined September 2026
Industry experience
- Software & Internet
- Financial Services
- Computers & Electronics
- Retail
Work experience· 5 roles
Delivered an automation framework featuring scripting and WebSocket-style communication for reliable integration and execution. Implemented components to orchestrate processes and support smooth end-to-end automation within the platform.
Built an end-to-end data platform using ETL pipelines, SQLAlchemy with PostgreSQL, a FastAPI backend, and Docker-based containerization. Focused on generating and synthesizing data for downstream use while ensuring the system could be deployed and scaled reliably.
Worked on LLM evaluation and trustworthy AI application development. Created and applied evaluation rubrics for LLM performance and quality, and supported system design for production readiness. Focused on integrity and reliability aspects of AI systems, aligning model behavior and outputs to measurable criteria and robust deployment practices.
Education
Certifications and awards
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