Getting into AI engineering: a practical path

“AI jobs” covers several roles: research scientist, machine learning engineer, applied AI/LLM engineer and data scientist. Most openings for newcomers are in applied engineering — building products with models rather than inventing new ones.

Core skills employers list

• Python and strong software engineering habits (testing, version control, APIs).
• Data skills: SQL, Pandas, data cleaning, evaluation.
• ML foundations: supervised learning, metrics, overfitting; PyTorch or TensorFlow for model work.
• LLM application skills: prompt design, retrieval-augmented generation (RAG), evaluation, cost and latency trade-offs.
• Deployment: Docker, a cloud provider, monitoring.

Projects that carry weight

• A RAG app over a real document set, with a written evaluation of answer quality.
• A model you trained, with a clear baseline, error analysis and what you’d do next.
• An end-to-end service: data → model → API → monitoring.

Check the skills listed in current AI jobs on Remotavia and compare them with yours using the skill analyzer; fill the gaps that appear most often.