A Software Engineer at InMobi works on high-scale, low-latency ad-tech platform components and mobile content delivery networks like Glance. Engine teams handle billions of ad requests and content impressions daily, requiring robust algorithms and fault-tolerant architecture. As part of this engineering group, you will design distributed systems, optimize data pipelines, and develop algorithms that process large volumes of data under sub-100ms SLAs. In this role, your technical decisions directly affect real-time bidding, user identification algorithms, ad serving pipelines, and content personalization engines. Engineers at InMobi work on core infrastructure, building distributed storage, high-throughput message streams, and mobile application frameworks across Java, Android, React, and Python ecosystems. ##### Tip InMobi evaluates candidate problem-solving speed and algorithmic rigor heavily. Expect interviewers to push for optimal time and space complexity, production-ready runnable code, and clear modular design. The position balances core computer science fundamentals with practical system engineering. Candidates should expect technical discussions around algorithmic trade-offs, system scalability, and practical architectural patterns.
Initial Screening
reportedThe 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 Data Structures & Algorithms (DSA)
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.
Online Assessment
reportedCandidates undergo a rigorous online assessment to evaluate technical capabilities.
What to demonstrate
- Candidates undergo a rigorous online assessment to evaluate technical capabilities
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Given a binary tree with random pointers alongside standard left and right child pointers, write a function to deep clone the tree.
- Answer aloud and timed: Implement operations to insert, delete, and search strings using a Trie data structure efficiently.
Technical Discussions
reportedSuccessful candidates progress through multiple rounds of deep technical discussions.
What to demonstrate
- Successful candidates progress through multiple rounds of deep technical discussions
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Write an algorithm to merge two sorted linked lists and reverse the resulting list in-place.
- Answer aloud and timed: Design an ad-serving platform architecture capable of mapping variable user identification tokens across multiple publisher requests at scale.
Hiring Manager Evaluation
reportedCandidates meet with the hiring manager for an evaluation of fit and skills.
What to demonstrate
- Candidates meet with the hiring manager for an evaluation of fit and skills
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Prepare two projects you led end to end, each with the decision you owned and what it cost.
- Have three questions about the team's roadmap and how success is measured in the first six months.
Behavioral Review
reportedFinal behavioral review to assess cultural fit and communication skills.
What to demonstrate
- Final behavioral review to assess cultural fit and communication skills
- Depth in Data Structures & Algorithms (DSA)
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 review above and write down what you would ask to confirm before it.
PracHub editorial advice for the preparation topics above.
Master runnable live coding
Practice writing complete, working solutions without relying heavily on IDE auto-completion. Interviewers look for clean syntax and logical code structuring.
Communicate your thought process clearly
Think out loud while solving algorithmic problems. If you hit a roadblock, explain your reasoning—interviewers will often provide hints if they understand your direction.
Brush up on core CS theory
Review DBMS normalization, OS process scheduling, and HTTP request lifecycles. These fundamental concepts are frequently asked alongside DSA problems.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Given an array of integers representing envelope dimensions, solve the Russian Doll Envelopes problem to find
Given an array of integers representing envelope dimensions, solve the Russian Doll Envelopes problem to find the maximum number of envelopes you can nest.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Find the length of the shortest path that visits all nodes in an undirected connected graph.
Find the length of the shortest path that visits all nodes in an undirected connected graph.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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 with random pointers alongside standard left and right child pointers, write a function to
Given a binary tree with random pointers alongside standard left and right child pointers, write a function to deep clone the tree.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Implement operations to insert, delete, and search strings using a Trie data structure efficiently.
Implement operations to insert, delete, and search strings using a Trie data structure efficiently.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Write an algorithm to merge two sorted linked lists and reverse the resulting list in-place.
Write an algorithm to merge two sorted linked lists and reverse the resulting list in-place.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Explain the Android Activity lifecycle, background thread execution options, and strategies for synchronizatio
Explain the Android Activity lifecycle, background thread execution options, and strategies for synchronization with backend data.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Describe operating system memory management, process thread scheduling, and deadlocks in multi-threaded enviro
Describe operating system memory management, process thread scheduling, and deadlocks in multi-threaded environments.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
How do you manage tight delivery timelines when project requirements are ambiguous or changing?
How do you manage tight delivery timelines when project requirements are ambiguous or changing?
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- 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?
Discuss your approach to database normalization, indexing strategies, and query optimization for high-throughp
Discuss your approach to database normalization, indexing strategies, and query optimization for high-throughput transactional databases.
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Why do you want to join InMobi, and how do your technical background and career goals align with our ad-tech s
Why do you want to join InMobi, and how do your technical background and career goals align with our ad-tech scale?
Approach
- Name the grain you start from and join outward from it.
- Check whether any join is one-to-many before aggregating, or the sums inflate.
- Say which index the query would use, and what makes it unusable.
- Handle the rows that do not match: that is usually the actual question.
Follow-up
- How does the query change if that join becomes one-to-many?
- What happens to this when the table is ten times larger?
Design an ad-serving platform architecture capable of mapping variable user identification tokens across multi
Design an ad-serving platform architecture capable of mapping variable user identification tokens across multiple publisher requests at scale.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Implement a Low-Level Design (LLD) for a rate limiter or search indexing mechanism using object-oriented princ
Implement a Low-Level Design (LLD) for a rate limiter or search indexing mechanism using object-oriented principles.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
How would you design a spatial database to hold map data and process geo-spatial queries efficiently?
How would you design a spatial database to hold map data and process geo-spatial queries efficiently?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Explain how you would implement a distributed transaction across two independent web services without direct c
Explain how you would implement a distributed transaction across two independent web services without direct communication channels.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Design and build a Google Search UI component using React, focusing on state management, debouncing, and web p
Design and build a Google Search UI component using React, focusing on state management, debouncing, and web performance optimization.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Explain HTTP protocol nuances, RESTful interface design, and how to optimize web applications for low latency.
Explain HTTP protocol nuances, RESTful interface design, and how to optimize web applications for low latency.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Walk through a complex project on your resume, detailing your specific architectural decisions and technical t
Walk through a complex project on your resume, detailing your specific architectural decisions and technical trade-offs.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Edge instances grow 400 MB per hour until the nightly restart
Edge API instances start at 700 MB resident and grow about 400 MB/hour; a nightly rolling restart has hidden it for weeks. Growth continues unchanged when request rate halves overnight, p99 degrades in the last hours before an instance is recycled, and heap used immediately after a forced full GC rises monotonically. The service holds no product state. Name the discriminating measurement that separates the plausible causes, give the most likely cause, and give the fix and how you would verify it.
Approach
- Separate resident memory from live heap first, because they fail differently. Resident size can grow from fragmentation, native buffers or thread stacks while the heap is flat; heap used after a full GC rising monotonically is the measurement that says objects are reachable and not being released. You already have it, so this is retention, not fragmentation, and that closes off half the candidate list.
- Use the rate's independence from traffic as the discriminator. Growth that continues at half the request rate rules out per-request objects that are merely slow to collect and points at a structure that grows with distinct values observed rather than with call volume. Write the candidates that have that property: a metrics registry keyed on a high-cardinality label, an unevicted cache, an interner, a per-key lock map.
- Take two heap snapshots an hour apart and diff by retained size, reading the dominator tree, not by allocation count or instance count. Expect one root holding a map with millions of entries, then follow the reference chain to the code that inserts and never removes. Allocation profilers point at churn, which is the wrong signal here.
- The candidate that fits this service is an observability label carrying an identifier, such as a request path recorded before templating so that /v1/resources/48213 becomes its own metric series. That grows with distinct ids seen, is independent of rate, and explains the late p99 degradation, since GC cost rises with the size of the live set.
Follow-up
- Post-GC heap is now flat but resident size still creeps. What are you looking at, and does it matter?
- How would you have detected this before an OOM, given the nightly restart masked the trend?
Built from the rounds and topics InMobi candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the InMobi loop
- Write out the reported sequence: Initial Screening, Online Assessment, Technical Discussions, Hiring Manager Evaluation, Behavioral Review.
- 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 5 reported rounds, with the weakest marked.
02Work Data Structures & Algorithms (DSA)
- Spend the session on Data Structures & Algorithms (DSA), which InMobi candidates report being tested on.
- Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.
Deliverable: One timed worked example in Data Structures & Algorithms (DSA).
03Work Problem Solving
- Spend the session on Problem Solving, which InMobi candidates report being tested on.
- Write one worked example in Problem Solving and time yourself on it.
Deliverable: One timed worked example in Problem Solving.
04Work Dynamic Programming (DP)
- Spend the session on Dynamic Programming (DP), which InMobi candidates report being tested on.
- Write one worked example in Dynamic Programming (DP) and time yourself on it.
Deliverable: One timed worked example in Dynamic Programming (DP).
05Answer out loud: Data Structures & Algorithms
- Answer aloud, timed: Given an array of integers representing envelope dimensions, solve the Russian Doll Envelopes problem to find the maximum number of envelopes you can nest.
- Answer aloud, timed: Find the length of the shortest path that visits all nodes in an undirected connected graph.
Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.
06Answer out loud: Systems Design & Low-Level Architecture
- Answer aloud, timed: Design an ad-serving platform architecture capable of mapping variable user identification tokens across multiple publisher requests at scale.
- Answer aloud, timed: Implement a Low-Level Design (LLD) for a rate limiter or search indexing mechanism using object-oriented principles.
Deliverable: Spoken answers to 2 reported Systems Design & Low-Level Architecture question(s), under time.
07Answer out loud: Domain-Specific & Core Fundamentals
- Answer aloud, timed: Explain the Android Activity lifecycle, background thread execution options, and strategies for synchronization with backend data.
- Answer aloud, timed: Design and build a Google Search UI component using React, focusing on state management, debouncing, and web performance optimization.
Deliverable: Spoken answers to 2 reported Domain-Specific & Core Fundamentals 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 situation where you had a major technical disagreement with a team member or lead and how you resol
Describe a situation where you had a major technical disagreement with a team member or lead and how you resolved it.
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- 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?
Unblock an engineer without taking the keyboard
A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.
Approach
- Ask before diagnosing, and ask for things answerable from data they already have: the attempt count on the job rows that produced duplicates, the handler's observed duration against its lease expiry, and whether the duplicate rows share a natural key that a unique constraint could have caught.
- Teach the shape rather than the answer. A lease cannot distinguish a dead worker from a slow one, so a handler that outruns its lease is running twice by design, and deploys deliver the other half by killing handlers mid-run on every rollout. Both of their candidate theories produce identical duplicate rows, which is why the evidence has to come from timings rather than from argument.
- Hand over a checklist they execute: a natural key on every write the handler performs so the second copy collides rather than appends, the record of intent written before any external effect, a lease heartbeat while running, and the metric that shows it working.
- Keep ownership with them deliberately. Pair on the first write, then step back; if you finish it yourself you have closed one ticket and left the same person stuck on the next redelivery.
Follow-up
- How would you distinguish a genuine double-delivery from a lease expiry using only the data already stored?
- Their handler calls an external endpoint before recording that it did. What do you tell them to change first?
Argue against a design, lose, and commit anyway
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
Approach
- State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
- Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
- Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
- Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.
Follow-up
- What threshold on that alert would have proved you right, and did anyone ever look at it?
- If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?
- 01
Describe a situation where you had a major technical disagreement with a team member or lead and how you resolved it.
- 02
A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.
- 03
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
How difficult are the technical interviews at InMobi?
The interviews are technically demanding, focusing heavily on DSA problem-solving and system design rigor. Most candidates spend 3 to 6 weeks reviewing algorithmic sheet topics—including graphs, DP, dynamic programming, and trees—prior to the interviews.
InMobi Software Engineer candidate reports ↗Are pseudocodes allowed during the coding rounds?
No, interviewers expect candidate code to be runnable and syntactically accurate. You should be prepared to compile, run, and pass test cases during the assessment and interactive rounds.
InMobi Software Engineer candidate reports ↗What distinguishes successful candidates in the system design rounds?
Successful candidates start by clarifying functional and non-functional requirements before presenting solutions. They quantitatively estimate scale, discuss trade-offs between storage technologies, and avoid presenting one-size-fits-all architectures.
InMobi Software Engineer candidate reports ↗What is the typical timeline from application to offer?
The hiring process generally takes between 1 and 3 weeks. Candidates participating in weekend recruitment drives often complete all technical rounds in a single day, with HR follow-ups occurring the following week.
InMobi Software Engineer candidate reports ↗How does team matching work for specific stacks like Android or Frontend?
While general SDE candidates go through standard DSA and backend system design rounds, domain-focused candidates (Android, UI/Frontend) complete specialized rounds evaluating framework architecture, lifecycle mechanics, and UI performance alongside core DSA evaluations.
InMobi Software Engineer candidate reports ↗What topics does InMobi test in interviews?
InMobi interviews most often cover Problem Solving, SQL, Data Structures & Algorithms (DSA), Test Case Design, and Data Analytics. The exact emphasis depends on the specific role you apply for.
InMobi 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.
- 01InMobi Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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