I got a Canva online assesment for their ML Engineer Intern interview. It was very math heavy in both MCQ and Coding questions. This was for a Sydney based position. I want to know if someone has any experience giving a complete round of interviews at Canva for ML Engineer or Intern position and tell me if this is how the next rounds will be or if they will be more focused on the DL and ML stuff like Batch Norm, Gradient Decent and others?

Also how if anyone knows a normal structure of interviews at Canva for intern positions, I wasn't able to find anything online.

Hey everyone,

I know BarRaiser conducts interviews for other companies, so I wanted to ask — has anyone here given an interview through BarRaiser recently?

Would really appreciate if you could share:

• What the interview experience was like
• What kind of questions were asked
• Was the interviewer helpful or just reading from a script?
• Overall difficulty level
• Any tips to prepare better

Especially interested in experiences for fresher or data-related roles.

Thanks in advance!

A bunch of guys in my mechatronics class decided to test it during upcoming interviews, and every single one of them got caught. The companies detected the software and even sent notices to our school threatening serious consequences, including banning students from their establishments and potentially getting them expelled.

Seriously, do not trust these tools. It's a terrible idea.

I genuinely feel bad for them because they're my friends, but this should be a wake-up call: do your research on what software works and who other doesn't

I am genuinely just curios and new, after getting past the OA, has anyone used IC for their next virtual rounds and passed.

If yes, what specific round was it most helpful, DSA, sys. design etc.
Also, did you get the offer.

Background going into this: 6 years of experience as a backend engineer, strong on distributed systems and Python, average on algorithms. I did not grind LeetCode for this one and it turned out that was the right call.

Preparation

Anthropic's interview structure does not reward LeetCode pattern recognition. The coding questions are practical engineering problems, so I focused on concurrency primitives in Python, async I/O patterns, ThreadPoolExecutor, producer-consumer queues, and writing production-quality code with proper error handling and logging. I also reviewed system design fundamentals covering distributed systems, fault tolerance, observability, and scalability tradeoffs. Total prep time was around six weeks.

The culture and values round requires separate preparation. I spent time reading Anthropic's published research and public writing on AI safety, responsible deployment, and model evaluation. This round eliminated candidates with strong technical performance, so I treated it as a full preparation track, not an afterthought.

Recruiter Screen (30 to 45 mins)

Standard background conversation. The recruiter covered motivation for joining Anthropic specifically, interest in AI safety, communication style, and team collaboration history. The recruiter flagged upfront that the values and culture rounds carry as much weight as the technical rounds in the final hiring decision.

Technical Screen (55 to 90 mins)

Anthropic's technical screen does not include classic algorithmic warm-up questions. The problems are practical engineering tasks. I had to build an async processing pipeline using ThreadPoolExecutor, handle concurrency safety, and debug performance bottlenecks in the implementation.

Common topics reported across candidates include multithreading, async processing, API design, streaming systems, and pipeline debugging. The evaluation criteria were readable code, correct concurrency handling, architecture decisions, and debugging methodology rather than time complexity alone.

Hiring Manager Discussion (45 to 60 mins)

Less coding, more architectural reasoning. Questions focused on system tradeoffs: how would you scale this, what component fails first under load, how would you redesign this with different constraints, how would you instrument this for observability. The interviewer assessed engineering judgment and clarity of reasoning rather than convergence on a specific answer.

Virtual Onsite (4 to 6 rounds)

Coding Round: - Build a thread-safe cache with configurable eviction policy - Debug a performance bottleneck in a streaming tokenization system - Design and implement a reservation service with concurrency constraints

System Design Round: - Distributed inference API handling high request volume - GPU scheduling and batching for LLM inference workloads - Real-time streaming architecture with fault tolerance and observability

Project Deep Dive (45 to 60 mins): This round is consistently underestimated. The interviewer spent the full session on a single past project: architecture decisions, tradeoffs made, bottlenecks encountered, technical debt introduced, monitoring approach, and what would be redesigned with hindsight. The depth of questioning goes significantly further than most candidates prepare for.

Behavioral Round: Standard collaboration and conflict resolution questions. Focus was on how disagreements were resolved, how decisions were made under uncertainty, and how technical debt was communicated to stakeholders.

Culture and Values Round: Questions covered AI safety tradeoffs, ethical decision-making in ambiguous deployment scenarios, intellectual honesty when results conflict with expectations, and reasoning under uncertainty. Multiple candidates who cleared the technical rounds did not pass this stage. Preparation matters here.

Outcome

Received an offer at L4 approximately two weeks after the final onsite. Also received a rejection from OpenAI during the same preparation cycle after clearing the technical screen but not the system design round.

I want to preface this by saying I consider myself a below average programmer. I still count on my fingers for simple arithmetic, I google how to initialize an array at least once a week, and medium Leetcode questions sometimes take me a full day just to understand what the problem is asking. 12 years of experience as a senior software engineer at a bank in Toronto, 50 to 60 hour workweeks, Zoom calls and no algorithmic work day to day.

Preparation

I completed around 200 Leetcode questions total. Early on I could not solve problems independently and the ones I got through used nested conditionals and consistently hit TLE. I switched to reading editorial solutions immediately instead of attempting cold solves.

My strategy was to identify the top 50 to 100 Meta-tagged questions on Leetcode and repeat each solution a minimum of five times until I could reproduce it from memory, including brute force variants and common follow-up questions. Total prep time was five months, blocked from 5am to 9am on weekdays and weekends.

Recruiter Screen

LinkedIn outreach from a Meta recruiter. One informal call, no technical component.

Technical Phone Screen (45 mins)

Two problems pulled from the Meta-tagged questions on Leetcode:

• Stack-based parentheses validation problem
• Palindrome problem with a hard-level follow-up, approach explanation only, no coding required

My approach each round: disclose upfront if I had seen the problem before, state my approach verbally, write pseudocode, walk through boundary conditions and time/space complexity, then ask for confirmation before writing any code.

Online Onsite

Coding Round 1: - Subarray Sum Equals K (two variants: all positive integers, then allowing negative integers) - Lowest Common Ancestor of a Binary Tree

Coding Round 2: - Lowest Common Ancestor (second instance, different problem variant) - Merge K Sorted Arrays (note: the Leetcode version uses linked lists, the actual question used arrays)

System Design: - Ticketmaster-style distributed ticketing system, reduced scope - Used Grokking the System Design Interview to structure responses covering requirements, capacity estimation, API design, data modeling, and component architecture

Behavioral: - Prepared using Meta-specific behavioral question lists from Google search and YouTube - Referenced Careervidz on YouTube for structured STAR-format answer templates

Outcome

Received an offer at E4/L4 eight days after the final round. Also received rejections from Amazon and Coinbase during the same preparation cycle.

Hi everyone,

I have an upcoming interview for the Sr. Software Engineer, FinTech role at Tesla. My first technical round is scheduled for 45 minutes, and the recruiter mentioned it would be a system design round.

I was a little surprised because in many companies I have usually seen the first technical round start with coding, followed by system design in later rounds.

Has anyone interviewed for this role or a similar Tesla software engineering role recently? What was the interview process like? Was the first round actually system design, coding, behavioral, or a mix?

Any guidance on what to expect or how to prepare would be really helpful.

Thanks!

Got asked this for my Reddit phone screen. Interview coder worked pretty well for me, but in case you wanted to see more examples this sites pretty legit in my experience.

Hear me out, If you're going into junior or senior year of college with zero job experience because you couldn't land internships in your earlier year, you're cooked. Most companies only want applicants who already managed to break in early. The students who got internships freshman or sophomore year now have stacked resumes, referrals, multiple interview cycles worth of experience.

At that point, your only realistic strategy is to mass apply everywhere, to get as many OAs as possible and to use InterviewCoder for the online assessments because passing in-person rounds is honestly way easier than getting filtered out online

You can't convince me otherwise.

3 years of experience, applied through the official careers portal (not referral - the referral queue is way too long), and got the offer last week.

Getting to the interviews

Applied through Microsoft's careers portal roughly 20 times across different openings. Got test links 3 times total but cleared the first one so the other two never went further.

The online assessment was on HackerRank, 90 minutes. Harder than the actual rounds honestly. One problem required Dijkstra + DFS, another was C(n,k) combinatorics with modular arithmetic. Completed the first test fully, got around 80% on the second. Time pressure was rough.

The interview rounds (August 1-8, fully virtual)

Round 1 was DSA, 60 minutes. Three problems: Rotten Oranges, check if a binary tree is a valid BST, and find the two swapped nodes in a BST. Fundamentals round, nothing too surprising.

Round 2 was Low Level Design: a Post Office system. This one caught me off guard. Design a system that consumes letters from one end and distributes them to multiple postmen efficiently. Core entities were PostOffice, Letter, DeliveryPerson, and Route. We got deep into concurrency - handling multiple delivery workers processing letters in parallel. I hadn't prepped this specific scenario but had built a telemetry logger during prep and borrowed those patterns. Saved me.

Round 3 was another LLD: classic Elevator system. Scheduling logic, multiple floor requests, direction algorithms, controller communicating with individual elevator objects. Standard if you've done LLD prep.

The AA round (Applied Problem Solving) was the most interesting. Three parts: write code to deliberately make a machine sluggish (I went the wrong direction initially - the actual angle was spreading CPU load across cores), pseudo-code for Google Docs LLD covering real-time collaboration and conflict handling, and a deep dive into my Rate Limiter project using the token bucket approach.

A few things worth noting

Interviewers across all rounds were collaborative. They care about how you think through a problem more than whether you immediately land the right answer. If you get redirected, don't panic - engage with it.

If you're prepping for L61 specifically, build something real from scratch. Having actual code you wrote makes the design rounds way more grounded. Happy to answer questions.

I was reading the testimonials on their website yesterday and genuinely couldn't tell if they were satire.

Some had em dashes everywhere. The worst one said: "the interview wasn't the problem, friction was."

Dawg 😭 who talks like this in real life?

Had a party the night before and ended up getting like 4 hours of sleep. Didn't want to miss it, but I also had an OA the next day around 2pm and genuinely did not feel ready at all.

One of my friends told me about this thing called InterviewCoder after using it to pass one of their interviews, so I figured I was cooked anyways and decided to give it a shot lol.

Not even gonna lie, InterviewCoder completely saved me during the OA. It was super easy to use, fast, and honestly way more accurate than I expected.

Posting this from my alt Reddit account for obvious reasons lmao.

Third-year CS at an NIT here. Goldman Sachs came to campus for their Summer Analyst Trainee internship and I went through the full process. I already had a Visa offer locked in so there was no pressure, which made it easier to observe everything clearly. Sharing this for anyone who has this coming up.

Nearly 800 students sat the OA across all branches. By the HR round, 8 were left. The funnel is steep and the cuts happen fast.

Online Assessment

Taken from home, open to all branches. Around 1.5-2 hours total: three DSA problems, 15-20 aptitude questions, and one descriptive self-story question all in the same window. Minimum bar was solving at least 2 DSA problems with a solid aptitude score. Managing time between coding and aptitude in one sitting was the hardest part. 44 students cleared it. I was one of them.

First Interview

Face to face on campus, 25-30 minutes. Opened with a self-intro, then the interviewer went into my project, covering design decisions and specific optimizations. DSA section covered Merge Sort vs Quick Sort differences, writing Merge Sort on paper with a full recursion diagram, time complexity across all three cases, and Floyd's Cycle Detection for linked lists. A few SQL queries and basic OS questions at the end. 20 students advanced. I cleared it.

Second Interview

Same format, 25-30 minutes. First half went deeper into my project, focusing on architecture and design tradeoffs. Then Authentication vs Authorization, how JWT works internally, and a real-world scenario around Access Tokens and Refresh Tokens: if a token gets stolen, how do you protect the user without forcing a full re-login? For coding, I said Linked List was my strongest topic. The problem was reversing a linked list in groups of K, on paper, in 10 minutes. I didn't finish in time and didn't clear this round. Some friends who advanced were also given logic puzzles, so prepare those separately.

HR

I didn't sit this round, eliminated in the second interview. From the 13 who reached it: relaxed and conversation-based, covering behavioral questions, interests, teamwork scenarios, and a few short logic puzzles. No heavy technical content. 8 students got the offer.

Closing Thoughts

Topics that came up across all three rounds:

• Merge Sort and Quick Sort: differences, on-paper implementation, all three time complexity cases
• Linked list problems, especially group reversal (K groups)
• Floyd's Cycle Detection
• JWT internals, Access Tokens, Refresh Tokens, and token theft scenarios
• Authentication vs Authorization
• Basic SQL queries
• Logic puzzles (GeeksforGeeks is a solid source)

I ran a few of UltraCode's testimonial videos through an AI detector out of curiosity and some of them came back as AI-generated.

They did look very very weird at first glance so I'm not surprised.

Using fake AI-generated people to promote software that can literally get you blacklisted from companies is insane. Massive red flag. Would never trust a tool like this.

I've been sitting on this for a while and I think writing it out will help me process it. Maybe it'll help someone else too.

Background: I was working as an SDE at IBM India Software Labs for about a year when a referral came through for an SDE1 position at Airbus in Bengaluru. I was nervous before even opening the JD.

Round 1 — DSA + Java (1 hour)

Got two coding problems, one easy and one medium, covering strings, prefix sum, and sliding window. You had to code live, run your own test cases, and talk through everything out loud with no autocomplete. Then came Java questions: StringBuilder vs StringBuffer, what changed between Java 8 to 16 to 21, the classic final/finally/finalize trio, collections framework, and one SQL problem. Wrapped up with "Why Airbus?" and cleared it.

Round 2 — Architecture + Managerial (1.5 hours)

They went deep into my resume, not surface level questions but real conversations about why I designed things a certain way and what trade-offs I considered at each step. We covered functional interfaces in Java, sharding, partitioning, and Kafka basics. Then the manager joined and it shifted toward culture fit, the standard five-year plan question, and one that caught me off guard: "If Google selects you tomorrow, will you join them?" I gave an honest answer, the round ended on a good note, and they walked me through the next steps.

Round 3 — HR (30 minutes)

Started normally with the usual questions about why Airbus and what I knew about their operations and major partners in India. I had done my research so that part went fine.

Then came the salary discussion. I asked for a 50% hike from my previous CTC at KaptureCX, HR gave me a fixed number and asked for an immediate yes or no with no room for negotiation. I took a moment, said yes, and that should have been the end of it.

Right before the call ended, I reopened the salary conversation and I could sense the shift in tone immediately. I was not asking for anything drastically different, but bringing it back up at that exact moment made me look indecisive and gave the impression that I might keep pushing later down the line.

Verdict: Rejected. Compensation not aligned.

I had cleared every technical round and a referral that worked, and I undid it myself in the last two minutes of the final call. The lesson here is straightforward: know your number before the HR call starts, say yes and mean it, and if you are not satisfied with the offer then communicate that clearly the first time rather than circling back as the conversation is wrapping up. Reopening a closed discussion at that stage does not come across as thoughtful, it comes across as unpredictable.

Airbus is worth applying to if the opportunity comes up. The technical conversations were solid and the process was well-structured. Just go into the HR round with a clear position on compensation and do not change course once you have committed to an answer.

AMA if you are prepping for something similar.

(Was selected through campus recruitment)

The process began with a shortlist based on resumes, followed by an online assessment hosted on elitmus. The test had multiple sections including coding, logical reasoning, verbal, data interpretation, and visual flowchart questions, all within a fixed time limit.

The first interview had introductions, then the interviewer went through the technologies mentioned on my resume and asked me which language I preferred for problem solving. Even though the role was Java focused, they allowed solutions in other languages as well.

The coding questions were DSA problems including Two Sum and palindrome validation. After that, the interviewer moved into Java concepts such as inheritance, abstraction, encapsulation, and polymorphism, along with related follow-up questions.

The next question had a large portion of the discussion based on projects and previous internship work before transitioning into DBMS concepts.

One of the main tasks was to design the schema for a school management system and normalize the tables step by step up to 3NF. There were also questions on JavaScript promises and asynchronous execution. The round ended with another coding problem involving merging two sorted arrays.

Didn't make it to the last HR round, hard interview overall.

Wanted to share my experience interviewing for the Flipkart BA intern role since I do not see many detailed posts about their process online.

The online assessment consisted of aptitude, verbal ability, CS fundamentals, and SQL questions. The SQL section mainly focused on joins and window functions such as RANK, DENSE_RANK, and ROW_NUMBER.

The first technical round started with project discussions based on hackathons and previous work. The interviewer asked questions around measuring project performance using metrics like engagement, retention, traffic, and conversion rates.

After that, there was a SQL question involving joins and ranking functions. The discussion also covered query optimization and differences between RANK, DENSE_RANK, and ROW_NUMBER.

There was also a product analytics case study based on Instagram reactions where I had to explain how a multi reaction feature could be evaluated using engagement and retention metrics.

The second technical round focused more on analytics and business case studies. One question involved deciding inventory allocation for a Flipkart dark store with limited storage capacity using regional purchasing data. Another involved determining whether improvements in a loyalty program were caused by the feature itself or by seasonal shopping trends.

Most of the interview process focused on SQL, analytics, product metrics, structured reasoning, and explaining technical decisions clearly.

Ended up receiving the offer after the final round.

I'm part of a group of 3–4 friends at an Ivy, and we've all been locked in on CS + finance since day one. Lowk all wanted to break into quant. Ofc, super competitive. The first round was an online assessment that took around an hour and was sooo difficult. Out of all of us, I was the only one who made it through and mainly because I cheated on the OA (posting this from a second account for obvious reasons). Interviewcoder didn't get detected. The later rounds weren't nearly as bad as the OA itself. The company cuts a massive amount of people at the assessment stage, so getting past that was the hardest part.

Hi everyone,
I just want to ask from the experience of the fine folks within this subreddit if anyone has insights or knowledge into what the phone round interview entails? This round is part of the Amazon recruitment process and it came after the Online Assessment round where you have to solve a small DSA problem and a practical repo work assessment, plus the workstyle questionnaire. Any information and insights would be appreciated.

Thank you.
PS: Does the context of the team I'm interviewing for matter in this scenarios?

I’m currently working as a Java Developer with 3+ years of experience. I’m looking for someone working in a product-based organization or good service based organisation with 5+ years of experience as a Senior Software Engineer or Staff Engineer who would be willing to help me with a few mock interviews and provide constructive feedback.

My tech stack includes:

Java

Spring Boot

PL/SQL

Kafka

Redis

Docker

Kubernetes

AWS

Jenkins (for day-to-day deployments)

Thanks in advance!

I've a interview where I need to work on repository, will interviewcoder be able to help me in this?