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AI Curriculum Developer Resume Example

For educators who can teach the mathematics and ship the notebook — and need a resume that shows both.

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What is a AI Curriculum Developer?

An AI Curriculum Developer designs what gets taught about artificial intelligence, and usually teaches some of it. That means sequencing machine learning concepts so they build on each other, choosing what to cut, designing assessment that measures capability rather than recall, and rewriting material as the tooling changes underneath.

The role sits across two professions that rarely overlap. Instructional design skill without technical depth produces courses that are pleasant and shallow; deep ML knowledge without teaching skill produces courses people abandon in week three. Employers screen for evidence of both, and completion and outcome data is the fastest proof.

Demand comes from universities modernising their programmes, bootcamps and training providers launching AI tracks, and increasingly from large employers building internal AI literacy. Titles vary — AI Curriculum Developer, AI Instructor, Technical Trainer, Learning Experience Designer — but they all reward the same evidence.

Key skills for a AI Curriculum Developer resume

curriculum design
instructional design
machine learning
Python
assessment design
learning outcomes
prompt engineering
large language models
AI literacy
workshop facilitation
teacher training
responsible AI
cohort delivery
learner mentoring
employer partnerships

AI Curriculum Developer resume example

Daniel Okafor

AI Curriculum Developer & Instructor

Manchester, United Kingdom

Summary

Educator and practitioner who builds AI curricula that people finish. 9 years teaching technical subjects, 4 designing AI and machine-learning programmes for university students and working professionals. Author of a 12-week applied AI course delivered at three institutions; 600+ learners trained at a 91% completion rate.

Experience

AI Curriculum Developer & Lead Instructor · Pennine Institute of Technology

Aug 2023 – Present

Designed and lead a 12-week applied AI programme covering ML foundations, prompt engineering and responsible deployment; 600+ learners at 91% completion.
Rebuilt assessment around portfolio projects rather than exams, lifting employer-reported readiness from 3.1 to 4.4 out of 5.
Partner with four regional employers to source real datasets, so every cohort ships work against a live brief.
Rewrote the generative-AI module twice in eighteen months to keep pace with tooling, without lengthening the course.

Associate Lecturer, Data Science · University of Salford

Sep 2021 – Jul 2023

Taught undergraduate machine learning and statistics to cohorts of 120+, with top-quartile evaluation scores.
Converted the ML module to a flipped-classroom format, raising seminar attendance from 54% to 82%.
Supervised 18 final-year projects, four presented at a national student research conference.

Data Scientist · Halcyon Analytics

Feb 2017 – Aug 2021

Built and deployed forecasting and classification models end to end for retail and logistics clients.
Ran the internal programme that upskilled 40 analysts in Python and applied statistics.

Education

MSc Computer Science (Machine Learning), Distinction

University of Manchester · 2015 – 2016

BSc Mathematics, First Class

University of Leeds · 2012 – 2015

Certifications

Fellow of the Higher Education Academy (FHEA)
PGCE — Post-Compulsory Education

Skills

Curriculum & Instruction: Curriculum Design · Instructional Design · Assessment Design · Flipped Classroom · Teacher Training

AI & ML: Machine Learning · Deep Learning · Prompt Engineering · Python · PyTorch · scikit-learn

Responsible AI: AI Ethics · Bias & Fairness · Model Evaluation · AI Literacy

Use this as your starting point

How to write a AI Curriculum Developer resume that stands out

Lead with outcomes, not topics. "600+ learners at 91% completion" tells a hiring manager more than any list of modules you have covered.
Show that you can still build. A recent project, notebook or model of your own is what separates you from a generalist instructional designer applying for the same role.
Name the assessment work explicitly. Designing assessment is the hardest part of curriculum development and the part most candidates leave out entirely.
Evidence that you keep material current. "Rewrote the generative-AI module twice in eighteen months" speaks directly to the fear that a course will be stale by the time it launches.
Include teaching credentials if you have them — FHEA, PGCE, or equivalent — near your degrees. For university roles they are frequently a hard filter.
Mention who you taught, not just what. Undergraduates, career-changers and senior engineers need genuinely different courses, and employers hire for the audience they serve.

AI Curriculum Developer resume — FAQ

Do I need a PhD to develop AI curriculum?

For university lectureships, often yes. For bootcamps, training providers and corporate learning, industry experience plus demonstrable teaching outcomes usually matters more. A Master’s with real delivery experience is a common and competitive profile.

How technical does the role actually get?

Technical enough to write the exercises yourself. You should be able to build the notebooks, debug a learner’s environment, and explain why a model behaves as it does. You do not need research-level depth, but you cannot outsource the content.

How do I show teaching ability without formal teaching experience?

Internal training counts, and so do workshops, conference talks, mentoring, and public material such as tutorials or open lesson plans. What matters is evidence that people learned something and that you measured it.

How do I keep an AI curriculum current?

Separate durable foundations from volatile tooling. Concepts such as evaluation, generalisation and bias change slowly; specific models and APIs change constantly. Courses that keep the two apart survive far longer — and saying so on your resume signals experience.

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