Survival Guide for Algorithm Engineers in the AI Era - Career Transition Handbook

A field manual for algorithm/ML engineers navigating the AI job market - written by a working practitioner, anonymously. Evidence-based, checklist-driven, zero fluff.

WHAT YOU GET (8 chapters, 40-60 pages)

• The real data: what the credible sources say is shrinking vs growing (WEF, IMF - every number sourced and linked)

• - A two-axis test to score your own subfield: does AI collapse your task or assist it? Do you own models or just call APIs?

• - The resume/portfolio system that survives AI screening (project narrative structure + minimum viable portfolio)

• - Moving into embodied AI / robotics ML: what interviewers probe, the 8-week plan for people with a day job

• - The 30-concept minimum set with pass/fail self-tests - not a question bank, a comprehension audit

• - The transition decision tree: internal transfer vs domain switch vs hold, honestly costed

• - Use AI to get an AI job: copy-paste prompts for JD gap analysis, adversarial mock interviews, job intelligence

• - Risk management: layoff signal reading, negotiation floors, the two numbers to write down before any scary decision

WHO IT IS FOR

Engineers and students whose field is being reshaped by AI - especially ML/CV/NLP people eyeing embodied AI, robotics, or AI infrastructure.

ABOUT THE AUTHOR

Anonymous senior algorithm engineer working in embodied AI, writing from the interviewer side of the table. No name, no employer, no promises - verifiable data and testable methods only.

PRICING: $1 on purpose - collecting the first round of honest reviews. If it disappoints, roast it in the product Q&A; that is what the price is for.

DELIVERY: instant PDF download right after payment (fully automated, works 24/7).

Support: message the store, replies within 24h.