Flynn Lachendro

About Me

I’m Flynn, AI Developer at Rubrical, where I design and implement AI systems that power our assessment tools. With a background in both research and applied machine learning, I help shape Rubrical’s core AI components — from building LLM pipelines to deploying scalable solutions that deliver real value to teachers and learners.

At Rubrical, I focus on turning cutting-edge research into practical tools that improve assessment workflows. I’m especially passionate about ensuring our AI systems remain transparent, reliable, and aligned with the needs of educators.

Development Approach

My development approach balances experimentation with robust engineering. I believe in designing human-centered AI systems that not only perform well technically but also respect the expertise of their users.

In educational settings, this means making sure our tools assist teachers without replacing their judgment — using automation to enhance, not undermine, the human touch in teaching and feedback.

What I Work On

• Designing and evaluating large language model (LLM) pipelines for assessment tasks
• Developing multi-agent AI systems to improve reasoning and feedback generation
• Implementing human-in-the-loop workflows for educational use cases
• Optimising model performance for accuracy, speed, and cost-efficiency

Outside Work

Outside of work, I’m a big lover of the outdoors and live music. I enjoy exploring new places and thinking about how technology can improve different aspects of life.

Background & Skills

• PhD, Biomedical Engineering, University of Strathclyde (CT scanning, immunohistochemistry, image analysis)
• Expertise in machine learning, LLM systems, cloud, and applied AI
• Experience across startups, R&D, and enterprise software projects
• Strong interest in education, healthcare, and science communication

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