AMD

Role: Senior Software Engineer (AI)

College: Not Specified

Interview Date: Not Specified (process started in 2024)

Interview Type: Full-Time

Result: Undecided (process delayed with a callback)

Difficulty: Not Specified (implied challenging)

Rounds: 5 technical rounds (including a hiring manager round)

Topics Asked: Resume-based project discussions, Graph-based problems, Machine Learning concepts (Activation functions, Regularization, Object detection, Residual connections, Non-Max Suppression, Transformers, Attention mechanisms), Data Structures, Algorithms, C++ (Smart Pointers)

Experience:

This interview process for a Senior Software Engineer (AI) role at AMD began with HR reaching out directly via LinkedIn.

Round 1: Technical Round (Resume-Based + Problem Solving) (60 mins) This round focused on the candidate's resume, discussing past projects, challenges faced, and implemented solutions. A graph-based problem-solving question was presented, which the candidate tackled confidently.

Round 2: Machine Learning Round (Resume-Based) (60 mins) This round was an in-depth exploration of machine learning concepts. Topics covered included activation functions (ReLU, PReLU, and their roles in deep learning), regularization techniques and their significance, object detection workflows, residual connections in neural networks, and Non-Max Suppression.

A waiting period of two months followed, during which the candidate raised concerns about job location preferences.

Additional Round (after callback): After the callback, an additional round combined Data Structures and Algorithms with C++ concepts. An easy DSA question was given, which the candidate coded efficiently in C++. The discussion then moved to C++ topics, specifically smart pointers and their usage.

Round 4: Machine Learning Round (60 mins) This round had the same interviewer as the previous ML round. Building on the earlier conversation, the discussion focused on advanced topics such as Transformers architecture and different types of attention mechanisms and their applications.

Round 5: Technical Round (Hiring Manager) (45 mins) This round was a hiring manager discussion, involving a thorough review of the candidate's resume and work in the ML domain. The conversation centered on contributions to past projects, technical skills, and how the experience aligned with the team's goals.

The outcome of the process was still undecided at the time of sharing, but the candidate described it as an enriching experience, emphasizing patience, preparation, and adaptability.