InstaDeep · Software Engineer
Updated · 2026-10-02

InstaDeep Software Engineer
Interview Guide

THE 60-SECOND BRIEF

The Software Engineer role at InstaDeep is fundamental to the company’s mission of enhancing AI capabilities across various domains. As a Software Engineer, you will contribute to the design, development, and optimization of innovative machine learning systems that power applications across industries. Your work will directly impact product functionality, user experience, and overall business success, making it a key position within the organization. At InstaDeep, you will engage with complex challenges that require both technical prowess and creative problem-solving skills. The projects you undertake will often involve collaboration with multidisciplinary teams, including research engineers and data scientists, to deliver cutting-edge solutions. This role is not only about coding; it’s about fostering innovation and driving AI forward in a scalable and efficient manner.

This guide is scoped to a Software Engineer candidate at InstaDeep.

InstaDeep candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

PythonGraph Neural Networks (GNNs)MHC Allele - Peptide Binding Prediction

18 min read

Browse Software Engineer questions

See the practice prompts

23Practice promptsAcross five skill areas

The Software Engineer role at InstaDeep is fundamental to the company’s mission of enhancing AI capabilities across various domains. As a Software Engineer, you will contribute to the design, development, and optimization of innovative machine learning systems that power applications across industries. Your work will directly impact product functionality, user experience, and overall business success, making it a key position within the organization. At InstaDeep, you will engage with complex challenges that require both technical prowess and creative problem-solving skills. The projects you undertake will often involve collaboration with multidisciplinary teams, including research engineers and data scientists, to deliver cutting-edge solutions. This role is not only about coding; it’s about fostering innovation and driving AI forward in a scalable and efficient manner. Candidates can expect to work on engaging projects that push the boundaries of machine learning and artificial intelligence, focusing on real-world applications such as healthcare solutions, gaming, and logistics. By joining, you will become part of a dynamic environment that values creativity, collaboration, and continual learning. InstaDeep

01

Initial Screening

reported

The process begins with an initial screening to assess candidate qualifications.

What to demonstrate

  • The process begins with an initial screening to assess candidate qualifications
  • Depth in Python

How to prepare

  • Be able to walk your CV end to end in two minutes, and say why this company specifically.
  • Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.
InstaDeep Software Engineer candidate reports ↗
02

Technical Interviews

reported

A series of technical interviews that include coding assessments and system design discussions.

What to demonstrate

  • A series of technical interviews that include coding assessments and system design discussions
  • Depth in Python

How to prepare

  • Answer aloud and timed: Describe how you would optimize a neural network for performance.
  • Answer aloud and timed: Can you discuss the trade-offs between different data structures?
InstaDeep Software Engineer candidate reports ↗
03

Behavioral Interviews

reported

Interviews focused on evaluating communication skills and teamwork.

What to demonstrate

  • Interviews focused on evaluating communication skills and teamwork
  • Depth in Python

How to prepare

  • Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
  • Re-read the description of the behavioral interviews above and write down what you would ask to confirm before it.
InstaDeep Software Engineer candidate reports ↗

PracHub editorial advice for the preparation topics above.

01

Structure Your Answers

Use frameworks like STAR (Situation, Task, Action, Result) to structure your responses during behavioral interviews. This will help you present your experiences coherently and effectively.

02

Study the Company’s Products

Familiarize yourself with InstaDeep’s products and projects. Understanding the company’s mission and how your role contributes to its success can help you articulate your fit during interviews.

03

Be Ready for Technical Challenges

Practice coding problems on platforms like LeetCode or HackerRank to sharpen your skills. Focus on algorithms, data structures, and problem-solving techniques that are relevant to the role.

04

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers about the team, projects, and company culture. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.

05

Follow-Up

After your interviews, consider sending a thank-you email to express your appreciation for the opportunity. This is also a chance to reiterate your interest in the position.

Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.

18 technical prompts0 include a worked solution

Write a function to determine if a string is a palindrome.

medium
Coding / Algorithms

Write a function to determine if a string is a palindrome.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Given a binary tree, how would you implement a function to perform a breadth-first search?

medium
Coding / Algorithms

Given a binary tree, how would you implement a function to perform a breadth-first search?

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

How would you merge two sorted linked lists?

medium
Coding / Algorithms

How would you merge two sorted linked lists?

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Implement a sorting algorithm and discuss its time complexity.

medium
Coding / Algorithms

Implement a sorting algorithm and discuss its time complexity.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Solve a problem involving dynamic programming.

medium
Coding / Algorithms

Solve a problem involving dynamic programming.

Approach
  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • How does this change if the input no longer fits in memory?
  • What is the worst case, and how likely is it on real data?

Built from the rounds and topics InstaDeep candidates report.

Small steps. Visible outcomes.0 / 7 completed
ONE WEEK · YOUR PACE

Prepare, practise & reflect

One practical outcome each day. Spend longer where you need it.

0 / 7 done
01Map the InstaDeep loop
  • Write out the reported sequence: Initial Screening, Technical Interviews, Behavioral Interviews.
  • For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.

02Work Python
  • Spend the session on Python, which InstaDeep candidates report being tested on.
  • Write one worked example in Python and time yourself on it.

Deliverable: One timed worked example in Python.

03Work Graph Neural Networks (GNNs)
  • Spend the session on Graph Neural Networks (GNNs), which InstaDeep candidates report being tested on.
  • Write one worked example in Graph Neural Networks (GNNs) and time yourself on it.

Deliverable: One timed worked example in Graph Neural Networks (GNNs).

04Work MHC Allele - Peptide Binding Prediction
  • Spend the session on MHC Allele - Peptide Binding Prediction, which InstaDeep candidates report being tested on.
  • Write one worked example in MHC Allele - Peptide Binding Prediction and time yourself on it.

Deliverable: One timed worked example in MHC Allele - Peptide Binding Prediction.

05Answer out loud: Technical / Domain Questions
  • Answer aloud, timed: Explain the difference between supervised and unsupervised learning.
  • Answer aloud, timed: What are the main considerations when designing a scalable system?

Deliverable: Spoken answers to 2 reported Technical / Domain Questions question(s), under time.

06Answer out loud: Coding / Algorithms
  • Answer aloud, timed: Write a function to determine if a string is a palindrome.
  • Answer aloud, timed: Given a binary tree, how would you implement a function to perform a breadth-first search?

Deliverable: Spoken answers to 2 reported Coding / Algorithms question(s), under time.

07Answer out loud: Behavioral / Leadership
  • Answer aloud, timed: Describe a challenging project you worked on and how you overcame obstacles.
  • Answer aloud, timed: How do you prioritize tasks when managing multiple projects?

Deliverable: Spoken answers to 2 reported Behavioral / Leadership question(s), under time.

Expand any day for tasks and deliverables. Your progress is saved on this device.

Behavioural rounds judge the decision you made and what it cost.

Describe a challenging project you worked on and how you overcame obstacles.

medium
Behavioral / Leadership

Describe a challenging project you worked on and how you overcame obstacles.

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you prioritize tasks when managing multiple projects?

medium
Behavioral / Leadership

How do you prioritize tasks when managing multiple projects?

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

Give an example of how you handled conflict within a team.

medium
Behavioral / Leadership

Give an example of how you handled conflict within a team.

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

What motivates you to work in the field of machine learning?

medium
Behavioral / Leadership

What motivates you to work in the field of machine learning?

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?

How do you ensure effective communication with team members?

medium
Behavioral / Leadership

How do you ensure effective communication with team members?

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What would you do differently if you ran that again?
  • How did you know your change caused the improvement?
  • 01

    Describe a challenging project you worked on and how you overcame obstacles.

  • 02

    How do you prioritize tasks when managing multiple projects?

  • 03

    Give an example of how you handled conflict within a team.

  • 04

    What motivates you to work in the field of machine learning?

PracHub preparation framework ↗
What is the interview difficulty like, and how much preparation time is typical?

The interview process at InstaDeep is generally considered average in difficulty but can vary based on your background and experience. Candidates typically spend several weeks preparing, focusing on both technical and behavioral aspects.

InstaDeep Software Engineer candidate reports ↗
What differentiates successful candidates?

Successful candidates exhibit a strong command of technical skills, effective problem-solving abilities, and the capacity to communicate ideas clearly. They also align well with the company's culture and values.

InstaDeep Software Engineer candidate reports ↗
What is the work culture like at InstaDeep?

The work culture at InstaDeep is collaborative and innovative, encouraging team members to share ideas and challenge each other to grow. Expect a dynamic environment with a focus on cutting-edge research and practical applications.

InstaDeep Software Engineer candidate reports ↗
How long does the interview process usually take?

The timeline from initial screening to offer can vary, but candidates can typically expect a response within a few weeks. The process is structured to provide timely feedback and keep candidates informed.

InstaDeep Software Engineer candidate reports ↗
Are there remote work opportunities or hybrid expectations?

InstaDeep offers flexible working arrangements, including remote and hybrid options, depending on the role and team structure.

InstaDeep Software Engineer candidate reports ↗
What topics does InstaDeep test in interviews?

InstaDeep interviews most often cover Python, Reinforcement Learning (RL), Machine Learning (general), Machine Learning Fundamentals, and Deep Learning (DL). The exact emphasis depends on the specific role you apply for.

InstaDeep Software Engineer candidate reports ↗
Sources & methodology 3 sources ↗

No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.