How I Used AI to Prep for Interviews While Working Full-Time

2026-07-09 · Source: Machine Learning on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Human Resources & Workforce Development · Depth: Intermediate, medium

Summary

The author successfully navigated a job search across five diverse companies, including quantum computing, big pharma, big tech, a medical imaging startup, and an AI company in real estate, securing three offers while maintaining a full-time role. Facing constraints of time and the need for precise, role-specific preparation, the author leveraged AI as a personalized coach. This involved using AI to identify relevant past projects for specific job descriptions, analyze interviewers' public work to tailor discussion angles, and critically review ML research papers for core theses and potential critiques. Additionally, AI facilitated mock sessions for open-ended systems design questions, providing specific feedback on communication clarity, and helped surface strong behavioral stories from the author's work history. The strategy emphasized providing highly specific context to the AI and iteratively refining its suggestions, rather than seeking generic answers.

Key takeaway

If you are an AI or Machine Learning Engineer preparing for interviews while managing a demanding full-time role, integrate AI tools into your prep workflow to achieve highly targeted and efficient study. Focus on feeding AI specific context like job descriptions and interviewer backgrounds to identify relevant project examples and refine your communication. Avoid generic prompts; instead, challenge AI's suggestions and adapt them to your authentic experience to prevent sounding inauthentic.

Key insights

AI serves as a powerful, context-aware interview preparation coach, enabling targeted and efficient skill alignment.

Principles

• Contextualize AI prompts for specific, useful output.
• Challenge AI suggestions; refine for authenticity.
• Focus AI on framing and connection, not answers.

Method

Provide AI with job description, interviewer details, and personal background. Ask for overlap, relevant examples, and potential discussion angles. Iteratively refine AI output into personal narratives.

In practice

• Paste job descriptions to map past projects.
• Analyze interviewer's articles for discussion points.
• Run mock sessions for systems design questions.

Topics

• AI Interview Prep
• Machine Learning Interviews
• Career Development
• Large Language Models
• Behavioral Interviewing

Best for: AI Engineer, Machine Learning Engineer, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Machine Learning on Medium.