As a Software Engineer at Indeed, you are tasked with building the infrastructure and features that connect millions of job seekers with their next career opportunity. You will work at a massive scale, where your code directly influences the global labor market and touches the lives of individuals searching for work, as well as the employers who rely on our platform to find talent. This role is critical to the Indeed mission of "We help people get jobs." You will contribute to complex, high-traffic systems that must be performant, reliable, and user-centric. Whether you are focusing on the Employer Jobs Platform, AI-driven matching, or core backend services, your work will involve solving unique engineering challenges, from optimizing search latency to designing scalable architectural solutions that support our global footprint. Success in this role requires more than just technical proficiency; it demands a deep commitment to the end-user. You will collaborate across cross-functional teams, including product managers and data scientists, to drive initiatives that make the hiring process more efficient and equitable. This is an environment where precision, clarity in communication, and a proactive approach to problem-solving are valued as highly as your ability to write clean, maintainable code.
Recruiter Screen
reportedInitial screening by a recruiter to assess your fit for the role.
What to demonstrate
- Initial screening by a recruiter to assess your fit for the role
- 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.
Technical Screening
reportedAssessment of coding and conceptual proficiency, often conducted via partners.
What to demonstrate
- Assessment of coding and conceptual proficiency, often conducted via partners
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: How would you verify the syntax of an equation while ensuring full test coverage?
- Answer aloud and timed: Explain the trade-offs between different data structures for a given storage problem.
Virtual Onsite
reportedSeries of back-to-back sessions covering various facets of engineering.
What to demonstrate
- Series of back-to-back sessions covering various facets of engineering
- Depth in Data Structures & Algorithms (DSA)
How to prepare
- Answer aloud and timed: Optimize a provided algorithm to improve its time and space complexity.
- Answer aloud and timed: Design a system for a company review platform where users can post and view feedback.
1 candidate reports. Individual accounts describe a particular role and hiring cycle.
Indeed Machine Learning Engineer Interview Experience — Indexing and Insertion in an Unrolled List
The author describes a tricky coding exercise from an Indeed virtual onsite involving a linked structure whose nodes each hold an array, an occupancy count, and a next-node reference. The first task was to retrieve an element using its position across the entire structure. The report discusses locating the relevant node and relates lookup cost to the number of nodes traversed. The second task add…
Read full experiencePracHub editorial advice for the preparation topics above.
Going into the loop without having done this.
Communicate your thought process: Our interviewers want to see how you approach a problem. Talk through your assumptions and reasoning before you start coding.
Going into the loop without having done this.
Drive the design: In system design interviews, do not wait for the interviewer to ask questions. Define the scope, clarify requirements, and propose solutions proactively.
Going into the loop without having done this.
Keep it simple: Start with a working solution and optimize it incrementally. Avoid over-engineering from the start.
Going into the loop without having done this.
Study your resume: Be prepared to discuss any project on your resume in extreme detail, including the challenges you faced and the technical decisions you made.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Write a function to construct a list of objects from a tree representation.
Write a function to construct a list of objects from a tree representation.
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?
Implement a solution for a graph-based problem using Depth-First Search (DFS).
Implement a solution for a graph-based problem using Depth-First Search (DFS).
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?
How would you verify the syntax of an equation while ensuring full test coverage?
How would you verify the syntax of an equation while ensuring full test coverage?
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 trade-offs between different data structures for a given storage problem.
Explain the trade-offs between different data structures for a given storage problem.
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?
Optimize a provided algorithm to improve its time and space complexity.
Optimize a provided algorithm to improve its time and space complexity.
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?
Review this component: what issues do you see regarding sorting order or data fetching?
Review this component: what issues do you see regarding sorting order or data fetching?
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?
Identify potential bottlenecks or security vulnerabilities in this search filter implementation.
Identify potential bottlenecks or security vulnerabilities in this search filter implementation.
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 the update path that detects a concurrent edit
resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.
Approach
- One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
- Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
- State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
- Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.
Follow-up
- A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
- Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?
Hold a per-tenant active cap against concurrent creates
A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.
Approach
- Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
- Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
- Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
- State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.
Follow-up
- A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
- The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?
Design a system for a company review platform where users can post and view feedback.
Design a system for a company review platform where users can post and view feedback.
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?
How would you architect an API for a CRUD-heavy inventory management system?
How would you architect an API for a CRUD-heavy inventory management system?
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?
What considerations would you prioritize when selecting a database for a high-traffic service?
What considerations would you prioritize when selecting a database for a high-traffic service?
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?
How do you approach scaling a service to handle sudden spikes in traffic?
How do you approach scaling a service to handle sudden spikes in traffic?
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?
Discuss the trade-offs between monolithic and microservices architectures in the context of our platform.
Discuss the trade-offs between monolithic and microservices architectures in the context of our platform.
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?
How would you refactor this legacy code to improve testability and modularity?
How would you refactor this legacy code to improve testability and modularity?
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?
How do you balance the need for rapid feature delivery with the necessity of technical debt management?
How do you balance the need for rapid feature delivery with the necessity of technical debt management?
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?
p99 jumped on one listing filter while p50 stayed flat
After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.
Approach
- Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
- Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
- Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
- Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.
Follow-up
- The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
- How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?
Built from the rounds and topics Indeed candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Indeed loop
- Write out the reported sequence: Recruiter Screen, Technical Screening, Virtual Onsite.
- 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 Data Structures & Algorithms (DSA)
- Spend the session on Data Structures & Algorithms (DSA), which Indeed 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 Indeed 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 Coding Practice (Algorithmic Coding Challenges)
- Spend the session on Coding Practice (Algorithmic Coding Challenges), which Indeed candidates report being tested on.
- Write one worked example in Coding Practice (Algorithmic Coding Challenges) and time yourself on it.
Deliverable: One timed worked example in Coding Practice (Algorithmic Coding Challenges).
05Answer out loud: Technical Fundamentals and Coding
- Answer aloud, timed: Write a function to construct a list of objects from a tree representation.
- Answer aloud, timed: Implement a solution for a graph-based problem using Depth-First Search (DFS).
Deliverable: Spoken answers to 2 reported Technical Fundamentals and Coding question(s), under time.
06Answer out loud: System Design and Architecture
- Answer aloud, timed: Design a system for a company review platform where users can post and view feedback.
- Answer aloud, timed: How would you architect an API for a CRUD-heavy inventory management system?
Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.
07Answer out loud: Code Review and Quality
- Answer aloud, timed: Review this component: what issues do you see regarding sorting order or data fetching?
- Answer aloud, timed: How would you refactor this legacy code to improve testability and modularity?
Deliverable: Spoken answers to 2 reported Code Review and Quality 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.
Tell me about a time you had to make a difficult architectural trade-off.
Tell me about a time you had to make a difficult architectural trade-off.
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?
Describe a project where you had to collaborate with stakeholders to define requirements.
Describe a project where you had to collaborate with stakeholders to define requirements.
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?
How do you handle situations where you disagree with a teammate’s technical direction?
How do you handle situations where you disagree with a teammate’s technical direction?
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?
What specific role did you play in the success of your most recent project?
What specific role did you play in the success of your most recent project?
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?
- 01
Tell me about a time you had to make a difficult architectural trade-off.
- 02
Describe a project where you had to collaborate with stakeholders to define requirements.
- 03
How do you handle situations where you disagree with a teammate’s technical direction?
- 04
What specific role did you play in the success of your most recent project?
How difficult are the coding interviews?
They are generally at a medium to hard level of complexity. We focus on problems that are solvable but require a clear, methodical approach and optimized solutions.
Indeed Software Engineer candidate reports ↗Can I redo the initial technical screen?
In many cases, candidates are offered the opportunity to retake the initial technical screening if they feel they did not perform to their potential.
Indeed Software Engineer candidate reports ↗How much time should I spend preparing?
Preparation time varies by individual, but we recommend focusing on consistent practice with data structures and system design over several weeks rather than cramming.
Indeed Software Engineer candidate reports ↗Is the interview process remote-friendly?
Yes, our interview process is designed to be conducted entirely virtually, utilizing modern video conferencing and collaborative coding environments.
Indeed Software Engineer candidate reports ↗What is the company culture like?
We pride ourselves on being a mission-driven, collaborative, and data-informed organization. We value engineers who are curious, respectful, and focused on solving real-world problems.
Indeed Software Engineer candidate reports ↗How hard is the Indeed interview?
Candidates most commonly rate Indeed interviews as medium, based on 710 reported interviews. About 39% of candidates who interview go on to receive an offer.
Indeed Software Engineer candidate reports ↗What topics does Indeed test in interviews?
Indeed interviews most often cover Stakeholder Management, Code Review, Behavioral Interviewing, SQL, and System Design. The exact emphasis depends on the specific role you apply for.
Indeed Software Engineer candidate reports ↗Is Indeed a good place to work?
Employees rate Indeed 3.5 out of 5 overall, based on aggregated workplace reviews spanning career growth, work-life balance, compensation, culture, and management.
Indeed Software Engineer candidate reports ↗Where is Indeed headquartered?
Indeed is headquartered in Austin, TX.
Indeed Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
Official role evidence, timestamped platform data and clearly labeled preparation advice.
- 01Indeed Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
candidate · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
platform · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
platform · Accessed 2026-09-22
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