Editor's Choice Q&A and Videos

I have worked at Meta my entire career (~5 years). I know that Meta is pretty "startup-ey" among the Big Tech companies, but I imagine that it can't mimic startups entirely and there's unique learning value startups can offer. Does switching to startups give big value to career development?

What's the right way to balance interviewing for FAANG roles when you have a full-time job? I've heard of people carving out their morning for an interview or interview prep, so dedicating 2-3 hours. Is this reasonable? What's a minimum amount of time I should spend on interview prep or interview every day?

This question assumes I don't have trouble getting interviews and have a few lined up. The prep I have in mind is the classic DSA/Leetcode, systems design, behavioural, mock interviews, etc.

I didn't interact much with people during my school and college years. Now that I'm stepping into a new phase of my life (my first job), I want to improve myself.

I'll have obvious reasons to interact with my teammates, so I'll try my best to socialize as much as possible (any suggestions are welcome). But how should I go about networking with people outside my team? Should I just randomly approach someone to introduce myself? When should I do it? When they are working they would be busy, so should I catch up with people during lunch (and what can I do if my whole team generally eats lunch together)? Will it be okay to go and sit or talk with a bunch of people having some conversation, or should I try to talk with individuals first?

Also, I'll be the juniormost folk there (other than maybe interns), how fine will it be to approach anyone random (since they can be very senior, which I don't know yet)? Even if I know someone senior to me previously (like the people I met during my internship), I find it hard to start a chat and find the right balance between disturbing them and having a conversation. And in general, I won't have much context to talk about the majority of the topics.

I know I'm really clueless, so any answers or resources would be highly appreciated!

I was curious to learn your take on strategies to push back when the expectations are not realistic. I want to expand my scope and feel that there is lot more scope for me to learn and navigate better. According to me, data and communication plays a major role here.

More specifically in my case, I am wondering how to account for me not being well versed with tech stack and constant context switching between clarifying requirements as they keep changing with each question of mine. How to politely and effectively communicate that although this may seem like a small increase of scope, given that I have to figure tech stuff it will be stretch.

Adding more context: It's trickier as I'm pretty new to the team and tech stack. I feel like I'm discovering a new requirement with every question I ask. I've set up recurring pair programming sessions to increase my velocity, but I'm not sure if that's enough.

Follow-up question: What research should be done before establishing the conclusion that expectations are not realistic?

I am a little worried about the potential of layoffs at Meta. I am not sure if I will get a needs support. I have been working on doing a design doc for the past month, and my manager has generally been very positive towards me. But I feel like I might get a NS due to my not submitting as many diffs and accepting as many diffs. I joined my team less than three months ago, and still technically ramping up. I would be sad if I got a NS or a pip, but it wouldn't destroy me.I guess my question would be how can I best buffer myself during these next few months, and how can I avoid situations like this in the future? What should I do if I do get put on PIP/NS?

I would like some info on how hiring decisions are made. I understand DSA and System Design are important but HMs know these aren't good predictors of performance so I see a disconnect there.

I'd like to understand what goes through the mind of the HM and/or committee before a decision is made.

I know it's a broad and complicated question that has different answers depending on the company, but any info is helpful.

I'm currently a frontend engineer at mastercard with 3 years of experience. I've been thinking about my next career move and do want to increase my compensation significantly within the next year. Outside a promotion, I can start leetcoding (I'm very out of touch atm) and try to land a higher paying job. But the other option is to learn blockchain and try to break into that field as it is more niche, maybe more high paying, and competition would be less too. But a quick glance at blockchain jobs on linkedIn wasn't very convincing as most jobs were asking for staff level devs. What do you guys think is the best avenue? Learn a niche technology or go the traditional route of leetcoding but has also has a plethora of competition especially in the current economy?

Appreciate your input!

Hi Taro Community

Just for backstory. I've been working for almost 4 years since graduating.

For my first two years, I worked at a big 5 company where I delivered and learned very little due to constant reorgs, politics, and toxic management. I wasn't performing and found a new job at a reputed, mid-size tech company.

Despite meeting expectations each cycle at this new company, I question if I truly belong in this field. I enjoy problem solving but I don't have a much interest in software as a craft (a trait that I see from top engineers on my team), nor do I really care about tech products.

I wonder if I'll have the longevity or motivation to stay in this field long term. (Companies don't want just average engineers like me, they want the best, most passionate people, right?) The good news is I have a great manager, team, and mentor right now -- all of which have helped me grow a lot despite all this.

I'm curious if there are some reframings or mindset shifts that some senior+ folks have made to make peace with or love their career path.

I've read enough answers on this platform to know that Alex and Rahul are huge fans of learning Android, both because it's a well-established area of tech (bigger than web) and because you can see how well your apps do. They always mention learning Android, but from my limited understanding, React Native gets you iOS and web as well, and is similar to regular web-dev (could totally be off here).

Isn't it more bang-for-your-buck to learn React Native and perhaps a better use of time?

I've heard people say that engineers should learn to cook and not just UberEats and Doordash food all the time. Sounds like a good idea from a health, cost, and relationship-building point of view!

That begs the question of what to cook. Am interested in any ideas! Like all engineers, I don't want to be spending too much time per day doing meal prep, but I'm sure once you do a few recipes a few times you can make them much faster.

Thanks!

In particular, what are the upsides of living in the SF Bay Area? Is it worth the high cost of living?

For my situation in particular, I would like to end up at Amazon working full-time after school, but I don't live in Seattle or the Bay Area (I live somewhat close to another major metro area). Does moving make sense?

Hey guys. Hope everyone is doing well. Also using AI/ML as an umbrella term throughout - feel free to correct if needed.

Into:

Senior Web Developer. Initially started from Software Development. Developed passion for Web Development and made the move. Worked my way up to Senior position. 70% backend, 30% frontend. Currently 80-90% IC, rest managerial responsibilities. 9.5 years overall. Changed companies over time. Been in various industries.

Problem:

Going back and forth about moving into AI/ML. Motivation - high interest and demand. Fear - leaving web development skills behind.

My Current Solution:

Ask reputable sources about AI/ML day to days and job responsibilities. Lots of it seems to be marketing and all that glitters is not gold.

If all checks out and my passion is rooted in evidence then I would like to take few Stanford machine learning courses online. Once fundamentals are solid would like to go for masters degree in applied machine intelligence or similar. Start looking for jobs.

Questions:

• Since this is one of my reputable sources - would you please describe a day to day/job responsibilities for an AI/ML engineer?
• Granted everything checks out - do you think going for Masters makes sense? Given that finances and time is not the problem.
• Would you say I have to leave a large portion of web development skills behind when making the move? What are some of the transferables?
• Would I have to start as an entry engineer? Do you think Masters helps here? Ultimately I would have to pass the interviews but then there is applying for the position and being considered for it afterwards.

These are all the questions I could think of. Apologize for the length, but thought it would be helpful to give context. Please feel free to include anything else you deem helpful. Much appreciated and Happy holidays.

I work with a team of 5 engineers amongst whom two are in my timezone. They always work overtime, work over weekends. They dont necessarily create a bigger impact but they are constantly posting on team chat groups about minor issues that they have seen and resolve it over the weekends. And stay late evenings and very late nights talking to the other team members. They spend a great deal of time obsessing over minor details like naming convention, doing repeated tasks.

I cannot keep up with this culture. I would actually like to have a personal life and spend some free time during the week working on side projects or learning something. At some point the opportunities do go to the people who have the most visibility right, no matter how mundane the work they do is? How do I navigate this? I would like to maintain a good reputation and work on interesting things. But I feel like I may be overlooked for promotions due to this. Any advice for me?

I often find myself in situations with engineers on the level above me (I'm a mid) where they are grasping the mental models, comprehending the code Infront of them and managing to remember a lot of context that helps them as they work through problems. I'm personally left feeling a bit dazed and confused. I was wondering if there are any more senior engineers here who recall having similar experiences when they were a lower level and how they overcame those feelings to move more productively through code when working with someone else.

What are some of the must read books for new software engineers which will prepare them for the real world?

Especially ones that can help me get acquainted with:

1. Writing high quality code
2. Design patterns (both high level i.e, system design and low level i.e, object oriented design)

My goal is to become fast at going from ideas to working solutions (thinking of approaches, thinking about organization of my code into functions, classes, etc).

I'm not sure exactly how to phrase this, but to give an analogy, I love card games (ex: Legends of Runeterra, Race for the Galaxy, Hearthstone, etc). There are a fixed set of rules and a fixed set of cards. I can "grind" games and get better by noticing patterns, picking up new strategies or tactics by playing against a diverse set of players. The outcome of an interaction is usually idempotent (i.e. card 1 interaction with card 2).

In real life, things are quite complicated. Asking a certain question in a certain way to person 1 and person 2 may give wildly different responses, and may even depend on your mood, their mood, your tone, time of day, etc. It's super messy and unpredictable.

I also feel a similar way about system design. The nearly infinite possibility of inputs, outputs, TPS, throughput, scenarios make it difficult to reapply the same set of rules to different scenarios. This is just talking about one component, when we bring in N components, the interaction gets very complicated and the "rules" change" case by case. I'm sure it gets better with practice, but I also feel I have a limited opportunity to learn or practice these on the job.

Has anyone found a way to structure these learnings in terms of a repeated "grind", because oftentimes I feel overwhelmed and don't know where to start. This is a complicated question, so answers regarding either a) soft skills or b) system design separately I will treat as valid answers.

I have a L6 equivalent MLE interview from a FAANG company.

Since last time I had interview for L4. I would like to understand what kind of quality difference does L6 show in an interview (coding/behavioral/system design -- ML)?

How would you demonstrate staff level quality in the interview rounds?