Lowe's

Typical interview loop

How Lowe's usually runs it for applied AI and LLM engineer roles.

1. 1

   Online assessment

   Focus: Probability and applied ML

   A timed test mixing probability problems with a small applied-ML coding task using a standard Python library.

2. 2

   Coding round

   Focus: DSA and coding fluency

   One or two technical rounds of easy-to-medium data-structures and algorithms problems, plus language basics.

3. 3

   ML and project deep dive

   Focus: ML workflow, metrics, projects

   Interviewers walk through the end-to-end data-science workflow and your past projects, including how you would design and measure a solution to a business problem.

4. 4

   Manager round

   Focus: Design basics and fit

   A technical manager covers basic system design, how APIs fit together, and how you work.

5. 5

   HR interview

   Focus: Motivation and culture fit

   A closing conversation about career history, motivation, strengths and teamwork.

Topics to prepare for Lowe's

The topics its loop weighs most, each with what interviewers check and what to study.

• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
• Evals and error analysisEvals
• LLM-as-judge: building and validating judgesEvals
• Eval datasets, benchmarks and evals in CIEvals
• Hallucinations: detection and mitigationEvals
• Design an eval: the live exerciseEvals
• Python for ML interviewsCoding
• Calling LLM APIs in Python: async, streaming, retriesCoding

How it weights your plan

Selecting Lowe's when you build a plan multiplies each topic’s priority score: