Our mentors are working engineers and researchers who rotate in from industry, so the material and the project briefs track what teams actually do right now.
ML Engineer · Recommender systems & ranking
Builds large-scale ranking and recommendation systems in industry. Mentors the Foundations and Data & MLOps tracks, with a focus on turning a trained model into something that survives contact with production traffic.
LLM Engineer · RAG, agents & evaluation
Ships retrieval-augmented and agentic LLM applications day to day. Leads the GenAI & LLM Engineering track and is opinionated about evaluation — “if you can't measure it, you can't ship it.”
Data Platform Lead · Pipelines & MLOps
Runs the data platform for an engineering org. Mentors on pipelines, feature stores, model serving and CI/CD for ML, and reviews every MLOps capstone.
Applied Researcher · Computer vision
Works on applied vision models — detection, segmentation and document understanding. Guides the Computer Vision & NLP track from first CNN to a deployed model.
Staff Engineer · Model serving & infrastructure
Owns inference infrastructure at scale. Teaches the LLMOps module: serving frameworks, batching, quantisation and the cost/latency trade-offs that decide whether a project is viable.
NLP Engineer · Information extraction
Builds NLP systems for extracting structure from messy text. Mentors the transformers and multimodal modules and runs the weekly NLP office hours.
MLOps Consultant · CI/CD for ML
Independent consultant who sets up ML delivery pipelines for teams. Brings real client problems into the Data & MLOps track as project briefs.
Product Engineer · LLM applications
Builds customer-facing LLM products. Mentors on turning a model into a usable product — guardrails, UX, telemetry and cost control.
Mentor rosters rotate by cohort. You'll meet your track's mentors on your kickoff call.