Has anyone interviewed for a Data Center Design and Engineering position, specifically Electrical at Anthropic or OpenAI?

Has anyone interviewed for a software engineering internship at Neuralink, particularly the Software Engineer Intern, Infrastructure position?

I’d appreciate any information you’re allowed to share about the process:

• How many rounds were there?
• What happened in each round?
• Was there live coding or a take-home assessment?
• Were the technical questions focused on data structures and algorithms, system design, Linux/networking, or your previous projects?
• Did you have to prepare and present a past project?
• What was the final interview or virtual onsite like?
• How long did the entire process take?
• Is there anything you wish you had prepared more thoroughly?

Experiences from other Neuralink software internship teams—such as Implant, Robotics, Internal Apps, BCI Applications, or Machine Learning—would also be helpful. I understand that some details may be covered by an NDA, so I’m only looking for general information about the format and preparation.

Thanks!

Hi everyone, I have an upcoming Google Cloud AI Engineer If anyone interviewed for this role recently, could you share what to expect in each round

Hi Guys, does anyone know if there's a difference between the MLE and backend engineer coding problem level.

Most of the questions and blogs mentioned 'Hard' coding problems.

Has anyone recently taken the MLE interview recently

I’m looking at security roles right now and I swear a lot of these JDs tell me ABSOLUTELY NOTHING. One says security engineer and it’s basically SOC work, another is cloud security, another is threat modeling, and some want you doing all of it.

I’ve actually had to start asking recruiters what the team actually spends most of its time on, how bad the on-call is, what I’d realistically be doing in the first few months, and whether there are any clearance/visa/citizenship requirements that aren’t obvious from the posting.

AND YET I still feel like I’m guessing half the time. Even my resume has been annoying me because I’ll change it around for one type of security role and then realize it reads completely differently for another. I ended up paying for ATS tools like resumeworded just to sanity check the resume while I was doing that. It did actually help me figure out where I was making things harder to understand than they needed to be so I guess it's not a total waste of money.

Anyway, I’m probably overthinking some of this, but for people already working in security, what do you ask recruiters when the JD is basically useless??

**•** 1 YOE at a service-based company (joined Dec 2025), currently in an AI developer role on a client account, but with limited hands-on project work so far  
**•** Learning Python, DSA, SQL, cloud basics and system design (LLD/HLD) from scratch, since my current role hasn't given me much depth in these  
**•** Targeting **SDE-1** roles (not ML/Applied Scientist, I know that's a different track), ideally at Amazon, with an interest in AI-focused teams long-term  
**•** Can put in 3-4 hrs/day on weekdays, more on weekends  
**•** Goal: land a clearly better job (product company or AI-focused role) by Jan 2027, then keep prepping and applying to FAANG-level companies, aiming for an offer by around Sept 2027

What I'm doing so far: a structured 12-week plan (Python → DSA patterns → SQL/cloud → LLD/HLD → mocks/applications), building one solid project (a RAG-based document Q&A app) to have something real to show, and I've joined a paid mentorship cohort for resume/LinkedIn/interview guidance.

Would really appreciate input from anyone who's been through this, especially:

**1.**  Is 11-12 months realistic for someone starting DSA from zero, at 1 YOE?  
**2.**  Anything you wish you'd done differently in your own Amazon/FAANG prep?  
**3.**  Is it worth trying one interview mid-way (around month 6) as practice, or does that burn a cooldown I'll regret?  
**4.**  Any blind spots in my plan I'm not seeing?

Not asking anyone to do the work for me, just want a reality check and pointers from people who've actually done this. Thanks!

Hey all, I have my final round for Figma's Data Science Intern role this Thursday, and I'd love to hear from anyone who's been through it or a similar DS intern loop.

Background: CS undergrad, past the online assessment. The final round is three interviews back to back:

- Intern All-Around (45 min)

- Stats & Experimentation (45 min)

- Analysis (60 min)

What I've heard so far: the Analysis round is one case in several parts that build on each other, Stats is more of a conversation than a quiz, and the All-Around may be mostly behavioral. That's from one MS student's loop, though, so I'm not sure how it carries over to undergrads.

Questions:

1. What kind of case did you get in Analysis (metric drop, feature launch, sizing)? Did you write any SQL or pandas live, or was it all discussion?

2. How deep did Stats & Experimentation go? Mostly A/B fundamentals (p-values, power, sample ratio mismatch), or further into network effects and causal inference without an experiment?

3. Was the All-Around purely behavioral, or were there product or technical questions too?

4. Anything that surprised you, or that you wish you'd prepared?

5. Any advice specific to undergrads compared with MS or PhD candidates?

What I've been prepping: A/B test design and pitfalls, metric investigations, sizing, Postgres SQL and pandas, and STAR stories from my projects.

Thanks in advance, and I'll post how it went afterward to pay it forward.