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Meta

Major Technology · US · UK · GLOBAL

13candidate experiences

Candidate experiences

What candidates experienced

Based on 13 candidate experiences.

Experiences vary by role, level, location and year. These findings describe the experiences in this dataset, not every applicant.

Filter experiencesRole, level, region, year and outcome

What stands out

Details a standard process page usually leaves out

Every pattern shows how many relevant experiences support it and how many contained the detail needed to assess it.

  1. 01
    Assessment styleAlgorithmic problem-solving

    5 of 9 experiences with assessment details

  2. 02
    Assessment styleAI-assisted work

    4 of 9 experiences with assessment details

  3. 03
    Assessment styleSystem-design trade-offs

    4 of 9 experiences with assessment details

  4. 04
    Candidate preparationExplaining decisions and trade-offs

    3 of 7 experiences with preparation details

Common process

How candidates moved through the process

These are stages and ranges reported by candidates, not a fixed company-wide interview route.

  • 9 of 11coding · 82%
  • 8 of 11behavioural · 73%
  • 7 of 11onsite loop · 64%
  • 5 of 11recruiter screen · 45%
  • 4 of 11system design · 36%
  • 3 of 11online assessment · 27%
  • 3 of 11technical screen · 27%

1–7 roundsReported among 9 experiences with round information.

Up to about two weeks to About one to two monthsReported among 6 experiences containing timeline information.

Assessment themes

What the interviews actually focused on

Each line uses only experiences containing relevant assessment detail, so missing information does not dilute the denominator.

Overall assessment style

  • 5 of 9algorithmic problem-solving · 56%
  • 4 of 9AI-assisted work · 44%
  • 4 of 9system-design trade-offs · 44%

Coding and online assessment

  • 5 of 12algorithms and data structures · 42%
  • 4 of 12practical implementation · 33%
  • 3 of 12general coding · 25%

System design

  • 3 of 8API and service design · 38%
  • 3 of 8system design · 38%

Behavioural and culture

  • 10 of 12behavioural discussion · 83%

Projects and case studies

Not enough similar experiences yet to show a common pattern.

Candidate preparation

What candidates recommend preparing

These patterns come only from experiences that included preparation detail.

  • 3 of 7explaining decisions and trade-offs · 43%

Communication and outcomes

How the process ended

Response

Heard-back and left-waiting findings use 11 experiences with a known response. Pending and unknown experiences are excluded.

Heard back10 of 1191%
Left waiting1 of 119%
Pending2 of 13Count among all included experiences
Unknown0 of 13Count among all included experiences
Blanked after interview0 of 100%

Communication patterns

  • 4 of 7The candidate reported receiving feedback. · 57%

Reported outcomes

Raw counts among 12 experiences with a reported final outcome. These are not hiring probabilities.

1Offers
8Rejections
3Ongoing
0Withdrew
0Declined or altered offers

Candidate findings

What individual experiences reveal

Each row describes one candidate experience and keeps its process, assessment and outcome context together. It is not a company-wide claim.

01

Candidate finding · Software engineering · Mid Level · United States

One candidate experience reported assessment focused on AI-assisted work.

Reported route

Recruiter screen → Online assessment → Coding → Behavioural → Onsite loop

Assessment focus

AI-assisted work · AI-assisted coding · API and service design · Behavioural discussion

Process shape

Full Loop · about 6 rounds · About one to two months · Recruiter Screen / Online Assessment / Behavioural

Communication and outcome

The employer replied. Outcome: Rejected

The experience placed emphasis on AI-assisted work.

02

Candidate finding · Software engineering · India · 2025

One candidate experience reported assessment focused on incremental testing and debugging and AI-assisted work.

Reported route

Recruiter screen → Online assessment → Behavioural → Onsite loop

Assessment focus

Incremental testing and debugging · AI-assisted work · Practical implementation · Debugging and code review · Online assessment · AI-assisted coding · System design · Behavioural discussion

How they prepared

Practical implementation · Company mission and product

Process shape

Full Loop · about 7 rounds · Timing was reported, but not in a consistent range · Recruiter Screen / Online Assessment / Behavioural

Communication and outcome

The candidate reported receiving feedback. Outcome: Rejected

The experience placed emphasis on incremental testing and debugging and AI-assisted work. Preparation guidance focused on practical implementation and company mission and product.

03

Candidate finding · Software engineering · Mid Level · United States

One candidate experience reported assessment focused on algorithmic problem-solving and system-design trade-offs.

Reported route

Recruiter screen → Coding → System design → Behavioural → Onsite loop

Assessment focus

Algorithmic problem-solving · System-design trade-offs · Algorithms and data structures · Data modelling and storage · API and service design · Machine-learning systems · Behavioural discussion

Process shape

Full Loop · about 5 rounds · Timing was reported, but not in a consistent range · Recruiter Screen / System Design / Behavioural

Communication and outcome

The candidate reported receiving feedback. Outcome: Rejected

The experience placed emphasis on algorithmic problem-solving and system-design trade-offs.

04

Candidate finding · Software engineering · Senior · United States

One candidate experience reported assessment focused on algorithmic problem-solving and system-design trade-offs.

Reported route

Technical screen → Coding → System design → Behavioural → Onsite loop

Assessment focus

Algorithmic problem-solving · System-design trade-offs · Algorithms and data structures · System design · Behavioural discussion

How they prepared

Behavioural stories

Process shape

Full Loop · about 6 rounds · Up to about two weeks · System Design / Behavioural

Communication and outcome

The candidate reported gaps between process updates. Outcome: Rejected

The experience placed emphasis on algorithmic problem-solving and system-design trade-offs. Preparation guidance focused on behavioural stories.

Dataset context

What is represented in this view

Coverage changes with the filters above, so the context stays attached to every finding.

13Candidate experiences
12Reached interview
8Full-loop experiences
1Role families represented
3Broad locations represented
2024–2026Interview years represented

Heard back among known responses10 of 11

Reported rounds · 9 with detail1–7

Commonly reported stagescoding · behavioural · onsite loop

Supporting employer guidance

Compare what candidates experienced with what Meta publishes

Candidate experiences are the main guide. Employer pages can corroborate or add context, but routes still vary by role, level and location. Last checked 1 Aug 2026.

Process: reported and published1 published route to compare

What the employer publishes

Treat this as a documented guide, then compare it with the candidate-reported stages and ranges above.

Selected published route

Published software-engineering route

allSoftware engineeringExperiencedChecked 2 Aug 2026
  1. 1

    Application and recruiter coordination

    Published stage

    online

  2. 2

    Technical screen

    Published stage

    video

    May assess: coding, communication

  3. 3

    Full loop

    Published stage

    video

    Normally four to six conversations of roughly 45 minutes covering coding, design and behavioural evaluation. The recruiter confirms the exact mix for the role and level.

    May assess: coding, system or product design, behavioural evidence

Published total timelineFull loop usually contains 4–6 conversations of about 45 minutes each.
Preparation and accessibility2 employer resources

What the employer publishes

Official preparation resources and support details can add role-specific context to candidate recommendations.

Communication and applicationsNo published policy detail

What the employer publishes

Published tracking and feedback policies describe intended support; candidate experiences show how communication was experienced.

No structured application tracking, contact or feedback policy is included yet.

PayBroad pay benchmark available
Levels.fyi benchmark available

This company-level page is not tied to one vacancy or level, so a broad figure is not presented as a role salary. Use a live-role comparison for a closer match.

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What current job ads disclose5 dated adverts checked
0/5salary disclosed
0/5working model disclosed
1/5closing date disclosed
0/5process disclosed
View the 5 sampled job adverts
Software Engineer, ProductNew York, NY · Menlo Park, CA · other US locations · checked 5 Aug 2026
View advert ↗
Software Engineer, InfrastructureLondon · checked 5 Aug 2026
View advert ↗
Software Engineer (Leadership), InfrastructureLondon · checked 5 Aug 2026
View advert ↗
Software Engineer (Leadership), Machine LearningLondon · checked 5 Aug 2026
View advert ↗
Employer links used8 employer links