General Motors software engineer candidates describe technical screens, coding assessments, behavioral discussions, and role-dependent system-design or software-knowledge conversations.
$127K
Avg. Base Comp
$153K
Avg. Total Comp
3-4 rounds
Typical Rounds
2-5 weeks
Process Length
General Motors software engineer interviews described here vary by team, but the clearest recurring preparation areas are coding, communication, and a detailed account of prior work. One candidate reported an HR screen followed by a manager programming conversation and two career- and domain-oriented discussions. Another described a three-question online assessment, then behavioral and technical virtual rounds; their technical discussion covered C++ fundamentals, object-oriented programming, memory management, and practical application design.
Algorithmic preparation may matter before later conversations. Candidates reported either an online assessment with easy through medium-hard LeetCode-style problems or a HackerRank-style dynamic-programming challenge. A separate technical screen asked the candidate to verbally explain an approach and how they would improve a program, so practice explaining trade-offs as clearly as writing code.
Behavioral interviews were consistently prominent in the relevant reports. Prepare specific examples from internships, projects, teamwork, leadership, and difficult working relationships, then expect follow-up questions about your reasoning and actions. One report also describes system-design and broad software-knowledge discussion during an onsite, while another frames nominal systems-design conversations as career background and domain knowledge rather than a formal design exercise. The available reports are limited and team-dependent, so prioritize adaptable preparation over assuming one fixed loop.
Synthesized from 6 candidate reports by our editorial team.
Had an interview recently?
Share your experience. Unlock the full guide.
Real interview reports from people who went through the General Motors process.
Share your own interview experience to unlock all reports, or subscribe for full access.
Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at General Motors
Design a data warehouse for a new online retailer
| Question | |
|---|---|
| Hurdles In Data Projects | |
| Duplicate Rows | |
| Testing Constraints | |
| Client Solution Pushback | |
| Payment Data Pipeline | |
| Decreasing Tech Debt | |
| Your Strengths and Weaknesses | |
| Evaluate News | |
| Bagging vs Boosting | |
| The Brackets Problem | |
| Google Maps Improvement | |
| Ticket Agent Analysis | |
| Target Indices | |
| Transformer Encoder Layer | |
| FAQ Matching | |
| Implementing the Fibonacci Sequence in Three Different Methods | |
| Search Timeout | |
| Matrix Multiplication | |
| Cloud-Agnostic Deployments | |
| String Palindromes | |
| International e-Commerce Warehouse | |
| Why Do You Want to Work With Us | |
| Processing Large CSV | |
| LRU Cache 1 | |
| 2nd Highest Salary | |
| Closest SAT Scores | |
| Employee Salaries | |
| Subscription Overlap | |
| Empty Neighborhoods |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report different openings: an HR screen, a video technical screen focused on background and verbally reasoning through code, or an online assessment. Two reports describe coding assessments with three problems or a dynamic-programming-style challenge.
Candidates report live or virtual technical conversations that may include practical problem solving. One candidate encountered C++ and object-oriented-programming discussion, including memory management and application design; another reported manager-led live programming.
Candidates consistently report conversational behavioral interviews. Questions may probe internship and project work, leadership growth, teamwork, challenges, and how the candidate handled relationships with coworkers; prepare concise examples and explain the why behind decisions.
Later conversations may include system-design, general software knowledge, or career and domain background. Candidates describe meaningful variation in how formal these discussions are, so clarify the team’s expectations while preparing to communicate design choices at a high level.
