AI / Machine Learning
Building and shipping models and the systems around them. The most hyped family on this site, and the one where we are most careful to be honest about entry difficulty.
Rarely a first tech job. Most people arrive here from software, data or infrastructure work.
Roles, easiest entry first
AI Evaluation & Red Team Specialist
You find out what a model does wrong before its users do, and measure it rather than guessing.
No degree needed
AI Governance Specialist
You work out whether the organisation is allowed to ship the model, and on what conditions.
No degree needed
Conversational AI Developer
You build the assistant, and you make it behave when a user says something you never planned for.
No degree needed
AI Infrastructure Engineer
You run the clusters models train and serve on — GPUs, schedulers, networking and the things that fail at 3am.
Degree usually expected
AI Platform Engineer
You build the internal platform other teams use to ship AI — so they do not each reinvent serving, tracking and deployment.
Degree usually expected
AI Product Engineer
You own whether an AI feature is actually good for the people using it — not just whether it runs.
Degree usually expected
AI Research Engineer
You build and run the experiments researchers design — training the models, not writing the papers.
Degree usually expected
AI Research Scientist
You originate the ideas — formulate the problems, run the experiments, publish the results.
Degree usually expected
AI Safety Researcher
You work on making advanced AI systems behave as intended — interpretability, alignment, evaluation.
Degree usually expected
AI Security Engineer
You find and close the ways AI systems get attacked — prompt injection, data poisoning, model theft, unsafe tool use.
Degree usually expected
AI Software Engineer
You are a software engineer who builds features on top of AI models — the AI is a component, not the product.
Degree usually expected
AI Solutions Architect
You design how AI systems fit together — and decide what not to build.
Degree usually expected
Data Engineer (AI/ML)
You build and run the pipelines that get data to the models, reliably and on time.
Degree usually expected
Distributed Systems Engineer
You build systems that stay correct when machines fail, networks partition and clocks disagree.
Degree usually expected
GPU / CUDA Engineer
You make code run fast on GPUs — writing and tuning the kernels that everything else waits on.
Degree usually expected
LLM Engineer
You build applications on top of large language models — retrieval, agents, evaluation and serving.
Degree usually expected
MLOps Engineer
You make machine learning repeatable — training, tracking, deploying and watching models in production.
Degree usually expected
Machine Learning Engineer
You take models from a notebook to something that runs reliably in production, and keep it working.
Degree usually expected
Only roles with a complete, verified route appear here. We would rather show you three real paths than sixty stubs.
Everything else we hold on this
The routes above are curated down to a handful each. The directory holds 571 more resources filed under AI & Machine Learning — courses, docs, tools and credentials, with what is actually free marked on each.