Career Advice About Meta

I recently joined Meta as a junior engineer and my hope is to be able to try out several domains (guessing realistically 2) to see where my interest lies. I’m not on an AI team currently, but given the rise of AI, I hope to be able to explore that area.

However, I understand that switching teams will disrupt my productivity and growth as a junior engineer. I’m wondering:

• When should I approach changing teams/domain? More specifically, is it better to change teams after being promoted to mid-level?
• How should I approach changing teams?

Background:

Our team inherited a set of products which are full of spaghetti code and bad design. We are currently building a high visibility and high impact project based on the backend of this system.

Although the main project UI goes on-track, some critical backend design flaws will hinder product performance and reliability within a couple of months - maybe close to or right after official product launch, which will turn our whole effort into a joke since we have executives' eyes on it.

My progress this year so far: (besides my roadmap item commitment)

• 1. Identified a system hotspot, finished analysis & design, and convinced our EM to rewrite this module (currently 95% finished by a junior engineer.)
• 2. Rewrote 1 foundation module to eliminate legacy design flaw (ended up with less code, less complexity, same performance, more system reliability.)
• 3. Design and rewrite another foundation backend module to address legacy design flaw & unblock development of the next milestone
• 4. Leading on technical design and discussion of a re-architecture for the overall backend end to end flow. (simplify design, improve performance)

NOTE:
- I tried to delegate 2 & 3, but no other engineers can do them after a few try since it's too tightly coupled with the rest of the system.
- our team lead is championing for all these work, which is how we are able to make room for them

Benefit of these work:

• accelerate other engineers' work in the system
• cut clean with the legacy system design flaw, improve product reliability and performance
• ensure our team's win on the high visibility project that built on top of this backend
• easier oncall for the short run or long run

My questions:

• In terms of performance review, my manager thinks this is better engineering work, while I think is closely tied to the success of our main project. What kind of evidence do I need to convince him? (My EM is not very technical)
• From his tone, I sense he thinks better engineering work in considered "lower priority contribution". Is this true? How do I communicate the importance of code/design quality with him?
• I'm trying to reach the staff level promo, does this initiative demonstrate any trait for the next level? (I'm not doing it for promo, but my EM's neglect on this makes me pretty frustrated because refactoring and rewrite is such tedious and painful work... I want to make it count)

Thank you!

Hi all, I'm currently working on GenAI server infra at Meta as an IC5. I'm interested in the space and have had a long standing interest to dig deeper into ML. At a high level, I'm considering the following:

1. Positioned well for E6 scope and exploring interest in people management (M1)
2. Taking an online masters program to brush up on math, ML foundation skills. This can better validate my interests. Alternatively, I can lean into online resources like Cousera, deeplearning.ai
3. Recruit internally as an E5 to a relevant team. Generally internal mobility empowers people to explore and learn new things. However, it helps to have relevant experience.

For online masters programs, I've heard of great things from Georgia Tech, with a ~$7k online program. Alternative options include UT and Stanford, and the latter is ~$60k. Rahul made a great video about his , but this would rather be a part time commitment, and I already have many YOE at Meta for my resume.

I'd also love to hear your general thoughts on navigating career moves into an area with existing, highly talented pool.

I'm a new MLE at Meta, so I'm in bootcamp. I'm trying to go for a team that’s super in-depth with regards to ML and neural architectures vs. a team that would give me more breadth. How can I find such a team and what questions can I ask to identify it?

I've shared feedback before with engineers more junior than me, and they didn't seem to take it well. They started avoiding our meetings afterwards - I feel like they thought their PSC was at risk. How can I prevent this situation from happening in the future when sharing feedback with E3s/E4s?

As an E5, I will have 1:1 meetings with E4s on the team to lead/mentor them. However, I find myself running out of time in the meetings sometimes - What can I do to make effective use of all the time?

How to build your reputation in new area?

How to use better story telling?

How to better align on the organizational goals?

I came into Meta with ~1.5 years of startup experience. I'm very good at Leetcode-type problems, so I was able to land an E4 offer. However, my prior experience mainly consisted of raw coding (E3-scope), meaning that I didn't have much experience developing E4 behaviors coming into Meta. This has led to me struggling on my current team where my manager let me know that I'm currently trending around MM. My team and manager have compounded this by being quite ambitious - I've gotten a lot of E4 EE+ scope with things like complex 0 to 1 projects (my manager is trying to get me to E5 ASAP). This is all hard to handle and has been a huge source of stress for me, so I'm currently considering other options.

Here's what's on the table:

• Stay on my current team and stick it out, trying to recover to MA by the next PSC.
• Switch to another team within Meta that's slower-paced.
• Job hop to Google as an L3. I was able to land an offer with them during my job search, and I kept that line open. I'm exploring team matching with them now.
• Go through some additional interview rounds with Google to get in as an L4.

Which of these is best for my career?

I've got my first interviews lined up with Meta and LinkedIn in December. I can probably push it to January but the dilemma remains the same.

How do I effectively prepare for those interviews?

Background : 2 years of SWE experience and Electrical Engineering background.

I am pursuing my master's from Georgia Tech part time and working a full time job. I barely get 4-5 hours for myself a week and I use those to either play football with friends or watch a show with my family.

I didn't expect to get such interviews in the first place. The recruiters had reached out to me.

After Thanksgivings and up until January first week, I have the semester break. So I can prepare them effectively for around 6 weeks with my job and no master's going on then.

I am not well versed with any topic to solve a question but I remember some of the concepts from my undergrad algorithms course and the weak interview prep I had done 3 years ago.

A good thing here is that I am pursuing a graduate level algorithms course this semester but again it's purely theoretical/psuedocode based. It helps building intuition with DP, Graphs and Divide N Conquer problems. On paper I can solve those questions but may fumble with the implementation.

I'm thinking of picking questions from the frequently asked Meta/LinkedIn problems list on leetcode and preparing for the Interviews solely based on this. I don't know if any other problem set would help me now.

I'm only giving this interview because I don't want to miss out on this opportunity. I've always dreamt of such an opportunity and now it's finally coming true. I wouldn't be sad if I didn't clear the interview but just disappointed in myself if I don't give my best in the limited time available.

Please do let me know if there is anything I can do to game the system and somehow perform well.

For example, knowing that we got EE- in people axis meaning that it's on lower end of EE.

I’ve recently been applying to various jobs, just in case of an unexpected layoff (golden parachute). Lately, I’ve been motivated to upskill as a developer. I’ve now reached the two-year mark at my company. After the reorg, I have a new manager, team, and director, and I really like this team. My performance over the past six months has been better than it was with my old team. Recently, Google reached out to me for an interview, but I haven’t really studied data structures and algorithms (DSA) due to work. My performance hasn’t been great, and now I also have a phone interview with Meta.

On the plus side, my company's stock has surged, and we’ve received bonuses, raises, and promotions. In my last 1-on-1 meeting with my manager, he told me I should be more independent and that my performance is great (hinting at a promotion)—fingers crossed. My family and friends are encouraging me to interview with both Meta and Google, but I don’t really want to leave my current company.

Hey everyone,

I'm new to Meta, and while I’ve enjoyed the onboarding experience and the sheer scale of the work here, I’ve found myself navigating through this incentive-induced rivalry culture.

On one hand, the competitive atmosphere can be motivating, but I also sense it might lead to employees chasing artificial metrics or competing for scope in ways that don’t always align with the bigger picture. Everyone talks about this, and I’ve caught myself wondering if I’m slipping into this mindset and whether it’s making me feel jaded.

There had been a few instance where a coworker would ship something that is half working, claim impact and then move off to a different thing, where I am left to fix and get it actually working.

Have any of you felt this way before? It feels less like I'm playing regular chess and more like I'm trying to navigate 5D chess—or maybe even alien chess! If so, how did you approach it without losing sight of the impact you truly want to make?

Looking for some candid advice or strategies to stay grounded and authentic while thriving in this environment!

A mixture of Silicon Valley and The Social Network is what inspired me quite a few years ago that pursing a start-up was even a possibility.

I even learnt the concept of what a "kanban" board was from Jared (played by Zach Woods).

Pursing this start-up ended up getting me into an incubator and then into a software job (after having no $ to continue the venture lol)

As someone who has never been to America, let alone the bay area and has never worked in big tech/a real start-up:

How close is the show to reality?

Met any Russ Hanneman types haha

How much of ML experience is needed/looked at during Team Match, if particulary interested in joining a team doing ML? Are Hiring Managers particular about this requirement during TM? This is for a E5 and E4 levels.

I’ve gone through Taro's courses on communication and asking questions, which were insightful, especially in showing how juniors can learn from senior engineers with deep expertise. However, as an MLE, I face different challenges and would appreciate some insights or thoughts from Alex or Rahul.

For context, I majored in math and hold an MS in ML from a top 3 university, so I'd say I have a solid grasp of both the mathematical and practical aspects of ML. Machine Learning can be deeply mathematical, often requiring formal training to fully get it. Some SWEs who transition into MLE roles may lack this foundation, and while they might have been excellent SWEs, the gap in math knowledge can hinder their abilities as MLEs.

Here are a few challenges I face with some SWE-to-MLE seniors:

1. Sometimes, my tech lead asks questions that suggest a lack of understanding of ML basics. While directly correcting them doesn’t seem right, what’s the best way to handle this?
2. This becomes a bigger issue when they set project goals that are mathematically infeasible. Without a strong math background, they rely on intuition, making it hard to guide them away from misguided directions.
3. Their informal grasp of ML can also complicate design documents by introducing unnecessary features that don’t align with the project’s objectives.
4. As seniors, they can get defensive and dismiss alternative ideas, which is frustrating, especially when I would need to work on a project with a high risk of failing.

I was working with a team during bootcamp, and they mentioned that they intentionally have very low test coverage (both unit and integration). This team is more on the back-end side. Is this a bad sign or is there something specific about Meta's culture that I'm missing here?

I just watched . Great material! In a couple of session, it was mentioned that Infra teams works differently, e.g. there is not as much XFN. Can you shed some light on how Infra team promo works?

• I've been reaching out to people via DMs and public workplace posts, comments on threads/tasks/diffs, sometimes email.
• Sometimes it takes 1 week to get a response or I just never get one, despite multiple follow-ups.

Unfortunately at a big company like Meta a lot of the stack is proprietary and are essentially black boxes, so I can't just search public documentation or use StackOverflow. Sometimes the documentation/wikis are outdated, so when the team maintaining it is unresponsive I have a hard time gaining traction with my projects. Ideally I'd try to go into the codebase to figure it out myself but it's hard to familiarize myself with another repo quickly especially if it requires special setup to get things running.

I also have a sample Workplace post that shows how I'm asking questions and looking for help: [REDACTED TO PRESERVE COMPANY CONFIDENTIALITY]

How to seek manager or TL’s support on project unblocking or career growth?

What topics I should talk in 1:1s with my manager/TL?

How to build the connections with leaderships?

I spoke to my manager about putting a promo packet up this half for an E5 promotion. I didn't rush into this. I've watched Taro's E5 promo crash course, have listened to my manager's feedback and consistently improved myself each time.

Now I feel ready. The Staff Engineer (TL) I work with has also vouched for me and said on the engineering excellence axis I'm performing way better than the other E5s on the team and he's not concerned about the other axes either. I've shared this with my manager. I've been performing at this level for about 2-3 months now and will continue to do so for another 2 months before perf season.

For some additional context, I joined Meta in Feb as an E4 and was aiming to get to E5 in 1 year. I know this seems aggressive, but that's because Meta down leveled me.

My manager said that I need to continue doing this for another half. Is this usually the case? Maybe I set my expectations too high by reading Alex's Linkedin Posts about mentoring engineers to E5 so quick :)

FYI on the internal career pages it says "1-2 quarters (or more)" which could mean absolutely anything

For the core workstream I got put on, there are a lot of potential angles to really move metrics, which I'm excited about. However, they mainly seem to be non-code solutions.

I've gotten earlier feedback that I need more coding signal, which has me apprehensive about this current workstream. I know that an E4 needs a lot of coding contribution for Engineering Excellence, but I am pushing for E5 which is more people/direction driven. Is it okay for me to take on this project or should I find something with more coding work?

I'm looking to get promoted to E4 in the next cycle, but I'm worried as my impact contribution isn't very clear. I've done a lot of work, but due to churn within my org (which includes a recent re-org), a good amount of my code isn't truly in production yet. I've documented my work in Quips and tasks to show that I did it, but I'm wondering if a lack of shipped impact will hold back my PSC.

Hi all, recently during Q1 roadmapping I chose to move on to a new workstream from a growth/independence point of view as part of working my way up to E4. (My earlier effort was a 1->100, this one is 0->1 and was decided by me, my TL and EM together), and I had a couple of questions about this move.

1. I have spent the past 6 months gaining context on a set of technologies and tools (internal to Meta) that perhaps only 2 other engineers on the team have context on.
   1. Should I do a knowledge transfer session or write up a doc to ensure all the context I have doesn't get lost?
   2. Should I allocate some time to supporting the team until I'm here on areas I gained context on?
2. There is some possibility of scope thrash since I'm also long-term supporting one of the projects part of the earlier workstream (I delivered the v0 and have been making iterative but small changes since then). Should I talk to my manager about this?
3. This is a very n00bish question: from a growth perspective, is it better to go 110% on the new workstream and all its nuances/open problems or go 80 and 20? As far as allocations go, I'm slated to be 100% on the new workstream as part of the roadmap.
4. Bonus question: should I do a year-in-review/look-back post in tandem with my self review? (This is a very Meta-specific question in a way, but would love to hear other views too!)