🤖 Varshith - AI Developer

Software engineering

• Python (functions, classes, typing, packaging)

  Evidence: Clean, reliable Python, Python from zero, Working with messy data

• Testing (pytest, mocks, fixtures)

  Evidence: Clean, reliable Python

• Git and GitHub (branches, PRs, reviews)

  Evidence: Git and GitHub for AI projects

ML foundations

• Probability, statistics and linear algebra for ML

  Evidence: Machine learning fundamentals, Vectors, similarity and probability

• Embeddings

  Evidence: Vectors, similarity and probability

• Supervised/unsupervised learning and evaluation metrics

  Evidence: Machine learning fundamentals

Evaluation

• Golden datasets and error analysis

  Evidence: Working with messy data

LLM engineering

• Tokens, context windows, sampling parameters

  Evidence: What AI is, in plain words

• Model selection and routing

  Evidence: What AI is, in plain words

Career

• Technical writing (README, design docs, blog)

  Evidence: Git and GitHub for AI projects