AlgoOlio

by Team Learning Machines

Your recipe for success in technical interviews

Introducing AlgoOlio

Through various multimodal deep learning techniques, AlgoOlio aims to gear programmers up in time for technical interviews by building computational thinking intuition and targeting gaps in domain knowledge.

Team members

Tan Pheng Yuan Ryner (CSD), Aayush Singh (ESD), Dian Maisara Binte Muhamed Iskandar (CSD), Dorishetti Kaushik Varma (CSD), Heng Jia Ming (CSD), Toh Wee Teck Dylan Mathew (CSD)

Instructors:

  • Javier Fernandez

Writing Instructors:

  • Belinda Seet

The Harsh Reality of Technical Hiring Today

The technical interview process for most software and tech roles typically unfolds across three critical stages, each filtering candidates more rigorously than the last.

  1. Resume Screening
    This is the initial gate where an automated system assesses your background, skills and experiences based on your CV. A clear, relevant and well-structured resume is crucial to advance past this stage.

  2. Technical Screening (OAs)
    Often the most daunting part of the process, this stage involves online assessments (OAs) or take-home coding challenges. Here, your problem-solving skills, coding proficiency and algorithmic thinking are tested under time constraints. The red highlights how challenging and notorious this stage is as many candidates struggle or get filtered out here thus making focused preparation essential.

  3. On-site Screening
    Reserved for shortlisted candidates, this phase typically includes technical interviews, system design discussions and sometimes behavioural assessments. It’s where your practical thinking and communication skills are examined more deeply by engineers and hiring managers.

Each stage demands a tailored preparation approach, but excelling in the technical screening round is often the key differentiator that propels candidates towards final interviews and offers.

What makes OAs so challenging?

At the heart of most technical screenings lies one major hurdle — Data Structures & Algorithms (DSA). Here is the multifaceted nature of why DSA is hard to master:

  • Complexity: Problems often involve intricate logic with multiple moving parts that are difficult to reason about under pressure.

  • Laundry List of Structures: From heaps to tries to graphs and segment trees, candidates are expected to recall and apply a wide variety of structures with precision.

  • Layers of Optimization: A brute-force solution isn’t enough. Interviewers expect optimised approaches in terms of both time and space that pushes candidates to balance trade-offs quickly.

  • Edge Cases: Even correct logic can fail if it doesn’t handle edge cases like empty inputs, duplicates or large datasets. These often become the silent killers in OAs.

Together, these challenges can cause even the most well-prepared candidates to underperform in online assessments, especially without timely feedback or strategic guidance.

Features!

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Acknowledgements

Team AlgoOlio would like to thank our Capstone instructors: Prof Javier Gomez Fernandez, Prof Oka Kurniawan as well as our Communications, Writing, and Reading Mentor, Belinda Seet for their valuable advice which were pivotal to AlgoOlio’s success. We would also like to thank the SUTD Entrepreneurship Centre for their support.

The team would like to thank our Entrepreneurship Capstone and Baby Shark Fund mentors, Chee Beng and Lily Phua for their valuable guidance and practical advice.

To all our mentors, thank you for your support, encouragement and guidance, which have been instrumental in the success of this project. Together, let’s shape the future of technical interview preparation!

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Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

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Contact the Capstone Office :

8 Somapah Road Singapore 487372

8 Somapah Road Singapore
487372

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Contact the Capstone Office :

+65 6499 4076

8 Somapah Road Singapore 487372

Welcome back!

Log in to your existing account.