Also called: On-Device AI Engineer, TinyML Engineer
Squeezes AI models down so they run directly on phones, cameras, cars and tiny sensors.
You shrink a speech-recognition model so it runs on a hearing aid without the internet. You test every version for speed, battery drain and accuracy.
Approximate: anchored on Bureau of Labor Statistics data for a broader job group.
Master's degree, about 6 years after high school. Bachelor's or master's in computer or electrical engineering.
Ways in: 4-year college, Graduate school. Training cost: $15k – $60k.
Majors to look at: Computer Engineering, Electrical Engineering, Computer Science.
Growing much faster than average. Rising demand as AI moves onto devices.
Low risk in 5 years, medium in 10. Running AI on phones, cars and sensors is a growing need; auto-compression tools help, but hardware limits keep experts busy.
Classes: AP Computer Science A, AP Physics, AP Calculus.
Official data: O*NET occupation 15-1252.
Career Universe is an early version. Pay, training and AI-risk figures are estimates to start your own research, not verified facts. The research was written with AI research assistants, checked by validation scripts and spot-checked by hand. Check anything important with schools, employers and official sources. How the numbers work.