SoFi

Typical interview loop

How SoFi usually runs it for applied AI and LLM engineer roles.

1. 1

   Recruiter conversation

   Focus: Background, role fit

   A phone interview with a recruiter if your experience fits; SoFi records and summarizes these calls with an AI tool unless you opt out.

2. 2

   Coding or skills assessment

   Focus: Coding fundamentals

   Depending on the role, a web-based skills test or programming challenge, taken before or after the recruiter call.

3. 3

   Technical screen

   Focus: Algorithms, problem solving

   An hour-long live coding round in a LeetCode style.

4. 4

   Onsite: ML deep dive

   Focus: ML theory, production ML

   A long session on ML theory, model design and production ML, anchored in your past projects and financial use cases like credit risk or fraud.

5. 5

   Hiring manager and team interviews

   Focus: Values, collaboration, technical depth

   Technical and behavioral interviews with the hiring manager and team, built around competencies tied to SoFi's values.

Topics to prepare for SoFi

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

• Behavioral interviews: STAR stories for AI engineersBehavioral
• Embeddings basics: word2vec, contrastive learning, what embeddings captureML fundamentals
• The project deep-dive roundBehavioral
• Story bankBehavioral
• Interview openers and closersBehavioral
• Python for ML interviewsCoding
• Calling LLM APIs in Python: async, streaming, retriesCoding
• Self-attention from scratchTransformers

How it weights your plan

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