Interviewing Q&A and Videos

I'm feeling very undervalued at my current position. I've been working on my service the longest and therefore was the one that onboarded most of my team. In 2023 my manager and tech lead have largely been too busy to help. For instance, I only have 1-1s one every 2-3 weeks. The new members we got on our team were new to the company and one in particular has relatively poor communication skills, so I have had to spend a lot of time onboarding them. Unfortunately, in my performance reviews the main emphasis is on the work that I am delivering and there is not much emphasis on the impact I've had through the rest of the team. But the couple of months I tried focusing more on my work, I noticed the culture on the team degrading. The hardest part for me has been that I have found my manager very unhelpful in helping me with my career and other frustrations. There have been multiple times where instead of helping I've felt as if he's blamed me. I have expressed this to them, but they have not changed. Now I'm in late stages of interviews with 3 companies. I estimate the pay increase would be between 10-25% if I receive an offer. Our team also just changed significantly, we swapped a mid-level engineer with a senior-engineer and got a new manager. They will be reporting to my previous manager so that manager will still be around. I'm optimistic that the new manager and teammate will upgrade my situation but given the more than a year of frustration without improvement I'm still leaning towards leaving. Though I am having second thoughts as well. I'd love to get any advice on how to handle my situation. Thanks so much!

One of the disadvantages of working at Amazon is that I don’t have enough experience working with Docker and Kubernetes anymore and frequently asked during recruiter calls if I know the technologies. I wrote a few Dockerfiles couple of years ago and I am pretty confident I will be able to pick it up if I have to use it on daily basis again. Should I be expected to know basics for tech interviews? What level of expertise should I have to say that I know docker and kubernetes to a hiring manager or recruiter?

Hi all. I have a verbal offer for a contract role. The recruiter said that they are going to send the official offer letter tomorrow. This company moved really fast and based on how fast they moved, they probably expect me to sign same day as receiving the offer. I am in the final stages for a couple of other companies. I sped up the interviews as much as possible but I can't imagine they can get me an official offer tomorrow. How should I handle this? I would like to finish these last interviews and see if I get an offer but the timeline is not lining up well. Update: I decided to take the offer. I talked to one of the companies that I am interviewing with. They said that they need over a week to get an offer out and they have two other candidates for the role. If I get a full-time offer, I will decide if it's worth it to renege the contract role. The market is so brutal that I don't feel comfortable risking my only offer, and I have no clue how the competition looks for the roles I am interviewing for.

Good morning! I work at a company of around 5000 employees and specifically on a team of 5. The culture and team are great but I feel bored half the time at work and don't see any true growth or progression happening. I work as the front end specialist on the team and feel a lot of the time my work has no impact as it only supports one customer. My other question is in the current market landscape and given my work isn't even on the medium scale how do I go about transitioning to larger companies and having more impact? For context, my current job takes about 40% effort to complete my work and sprints ahead of schedule. Thanks!

I read or saw a video a long time ago that when you negotiate, you want to have competing offers so that you can stack them against each other. That being said because different sized companies have different pacing for the application process i.e. big tech can take a lot longer whereas startups might move a lot quicker, there are optimal times for when you should apply -- e.g. applying to big tech first and then applying to startups around the time you start entering your FAANG interviews. Generally speaking, what is the correct timeline for applying to big, medium, and small sized companies? Thanks

I just began my job search and I haven't been hearing back. I’ve sent out over 250 applications in the past month and haven’t received a single callback or online assessment. I’ve had my resume looked over by more than five Taro engineers, and I've been told its strong, competitive, and looks good. I’ve landed interviews before, back in 2023 and 2024, so I’m really puzzled as to why I’m not getting any responses now. I have around three years of experience and I'm targeting junior to mid-level positions and applying to only jobs posted in the last 24 hours I know referrals are king, but trying to get some "low tier" companies in the loops first before getting referrals to bigger companies My 1 guess is its probably the volatile economy with the tariffs, increased prices, and stock markets crashing. But not sure if its just a me problem or if others are getting Follow up Q: Do people open links on cold emails? I have seen people send like loom recordings to HMs of their side project. But im not sure if anyone would even open them. TL;DR: whats the best way to get noticed in this tough market? (Assuming you already have a cracked resume)

I am a new graduate working as a data scientist at a mid-sized company. I'm wondering about the importance of LeetCode for data science interviews. I'm comfortable with SQL and can handle hard-level SQL problems, but I struggle with medium and hard-level coding questions (non-sql/algorithm style) on LeetCode. On the flip side, I am very comfortable with ML and DL algorithms. Should I focus more on building ML/DL projects or on mastering medium and hard-level LeetCode problems?

This whole train of thought started after a coffee chat with a family friend who is an Engineering Manger at FAANG where she told me that she thought I was getting too comfortable and that I needed to start working on harder problems to keep learning. In my current role (my first and only job since graduating college in May 2022), I work with prospective F500 Banking & Insurance clients to engineer small scale POCs that prove the value of IBM’s technology, and to hopefully convince them to complete the sale. I was originally hired with the title “Data Scientist” but noticed that my customers were largely uninterested in IBM’s Cloud Platform ML offerings and were already using other hyperscalers. Following the release of ChatGPT, client interest in IBM surged and we have had much more business as clients stand up our Generative AI Studio offering (watsonx) vs others (think Vertex AI, Azure ML, Sagemaker). In January 2024, the business updated my title to AI Engineer to reflect this change, and I work almost completely on LLM related deals now, and almost never with “classical” ML. The primary technologies I am responsible for are: Generative AI Studio, Data Lakehouse (including vector DBs), Data & AI Governance & AI Virtual Assistants (chatbots). I would say that my role consists of 50% Business Development and collaborating with sales & account teams to develop and progress sales opportunities and 50% hands on the keyboard engineering. None of the POCs we develop are architected with deployment in mind, as IBM also has a consulting business that they promote for that. Ideally the client is billing consulting hours, and my team costs nothing so we should build as fast as possible. For some context, in college I was largely unsure what I wanted to do afterwards, and joined IBM quite literally because I was a senior who was about to graduate with no job, and I knew someone who worked at IBM sales that offered to help me. That was the first time I ever thought I might go into tech. I went to an Ivy League school where I earned a BA with a joint major in a Social Science + Statistics. The stats I learned were much more applied than theoretical, and despite having the degree, I would say that I lack the necessary mathematical foundation that one would expect of an MLE or Data Scientist, including key topics like Linear Algebra, Stochastic Processes & Discrete Math etc. I did take one intro ML + NLP class, but it was extremely general and not mathematical (although it thankfully helped me fake my knowledge to pass my IBM interview). I also didn’t take any CS courses except one intro Java class. I know what my classmates at FAANG earn, and their entry level base salaries are at least 50-60k higher than mine. I also do not have any equity in my compensation package, which I know will make the real difference in the long term. IBM is making a concerted effort to reduce our workforce size. Despite being a high performer with consistently good feedback from my manager & colleagues, I don’t think that I will earn that first promotion soon to close that salary gap between IBM & FAANG. Luckily, I don’t see myself getting laid off soon either, so there is no urgency to make decisions. This company definitely gave me a shot when others probably would not have given my background and Data Science skills at the time. I feel like I have spent the last two years faithfully giving them as much as I can and also learning a lot for myself along the way, but now is the appropriate time to start thinking about where I really want to go in the future. I feel like the Data Scientist position I was originally hired for required a certain level of mathematical foundation that I had, but that building with pre-trained models definitely does not require. I had skills that were relatively harder to develop and somewhat in value, but now prompt engineering can be taught in almost a day, and one can quickly learn the adjacent tech stack to build and deploy with LLMs without much math. I thus feel anxious about tying my future to this, as my market value would naturally be a function of how hard the skills I have are to acquire. The AI Engineer role requires more of a Software Engineering background to really integrate the LLMs into apps than a math background. I could also keep focusing on learning more math and get into the model training & research side, which is an option I am considering too. Despite landing here by accident, I learned that I really like big tech, and I think I actually want to end up in a Sales role as well. I am told by my manager that clients give positive feedback about working with me, but I observe that the best sellers who earn the most money in IBM are the ones with deep technical expertise AND who also have the soft skills to become trusted by the clients. These people often worked on product teams or in highly technical roles before finishing in Sales, which is what I think I should do too, as my knowledge base is too broad to really become a technical expert, and the POCs I build are too short to have any knowledge of how to actually deploy these technologies into production. I would thus like to end up at a FAANG company and make more money, and probably work on an AI product team either as a SWE/Data Scientist or potentially even as an AI researcher (though I’m not interested in a PhD, which I know is important). My question for you all is what would be the best path for me to get there? Should I focus on studying more math and to try for a Data Science/MLE role, or should I try to focus on learning Software Engineering & patching up my math with supplementary self-paced courses. My initial hunch is go back to school for a 1 year Masters in CS, and take a few math courses beforehand & maybe some more math based deep learning or transformers focused courses while there. This would ideally make me suitable for SWE or DS/MLE/AI Engineer roles, and expand my chances of success. Most American schools require CS bachelor’s degrees and their applications have closed, but this masters program in the UK at Imperial seems open. Does this program look like useful material for someone in my position to learn (link)? I feel like I have half the math and half the programming experience to succeed, but am not knowledgeable enough at either to really do as much damage as I know I am capable of. I would be keen to hear from some of you more experienced veterans out there how you think I should proceed. I have been living at home with my parents and saving money, so I could pay for the masters and assuming I make it into FAANG the extra salary would mean the degree pays for itself in 1.5-2 years. I could go on educational leave and my job at IBM will likely be there for me should I fail to get recruited somewhere else (IBM recently stopped paying for masters degrees unfortunately). I also know that there is opportunity cost of not earning for 10 months while at school. Given my context and situation, the main questions I want help thinking about are: Given the way the industry is moving and my experience, which kinds of roles should I aim for? Should I try to earn the masters, or should I try and self-study either math or software engineering while at IBM and recruiting slowly If I go the school route, would I have enough time to be able to pass an interview in Fall 2024 when I start (since I would need to recruit right away) if I started preparing now, or should I wait until the next application cycle and start in Spring/Fall 2025. I know this was long, thank you so much for reading, and thank you in advance for your help. Hindsight is 2020, but I am young and I don’t fault myself for not knowing what I wanted to be when I grew up. I know with hard work and patience that I will get there.

In a recent behavioral mock interview, I was asked the question "Tell me about a time you motivated a colleague in your team." From my understanding, the question's focus appears to be on teamwork and collaboration. A story I had was when a colleague in my team was struggling to meet deadlines for a group project and complete his work due to him having multiple upcoming exams in a short timespan. I proactively approached the colleague for a 1:1 conversation to listen to their concerns and empathized with his struggles, understanding how tough it was for him to balance multiple priorities. I then suggested to collaborate on the project and offered to help him with some of his tasks so he could focus on the ones most important for the project. After communicating with the team, I assigned him the task of identifying and fixing a tricky bug in our system, as debugging was one of his key strengths, and this allowed him to focus on what he did best. My colleague became more motivated to contribute to the project by working on a task tailored to their strengths. This approach not only helped the project stay on schedule, but also reduced their stress and boosted overall morale and team productivity. Do you think this answer is on the right track? I would gladly appreciate any thoughts or feedback on this answer. Big thanks for reading through all of this - I know it is a very long post and I really appreciate your time!

I'm currently happily employed and I want to cultivate a strong network so that when I need a new job in the future, I am not struggling I have watched the Taro course on referrals and cold emailing, but my issues is that I went to a small no-name state school and I don't know that many alumni. Also work at a 5-10 person YC backed startup so I don't interact with many people at my job I understand networking is a long term game, but I feel stuck trying to build deeper relationships and especially trying to level up I'd love something actionable on how I can add value to people and network that doesn't rely on my job/college I'd also love to know how to leverage the fact that I work at a YC backed company to network with other YC backed startups? Everyone wants to work at a YC backed company so I worry that the eng leads/founders get tons of spam email, so how can I stand out -- especially if they are a B2B company where I cant use their product and offer feedback or if they're more mature (series A/B) and I don't really have a lot of feedback

Hi, I last posted here: . I’m a junior since I have 1-2 YOE and my bachelors in comp sci from NYU is outdated from 2019. Some people think I should go for a masters maybe in AI / ML or security or some other specialization to try to get back into the industry. Since I mainly worked with JavaScript / TypeScript and React and some Python / Ruby on Rails, do you recommend sticking to that stack or picking up something new altogether like mobile (I prefer iOS over Android) when it comes to implementing my ideas? I recently completed some free hire train deploy program over 10 weeks that uses Java SpringBoot mainly in order to land a job via one of there clients. I last worked at Civis Analytics, a data collaboration company from November 2021 to December 2022 before getting laid off due to company downsizing using JS / TS on the frontend and some Ruby on Rails, Docker, and AWS on the backend. As a web dev at West Point, I utilized tech such as Vue and Flask but I didn't get to do much as they didn't have version control set up so I quit after working on some mocks after 6 months. I haven’t really been getting interviews since failing the Meta L4 interview. Thanks.

I currently have 2-3 side projects that are OK. They had some usage, shows my skills in building non trivial software. But it feels like if a project doesn't have 10k users then its pointless in this market and I feel hesitant to do a project because I have this go big or go home mentality Also 10k users feels like such a massive goal and if im not able to hit it then all the hours spent is wasted. There's also no gaurantee that the project will ever hit 10k users. Plus getting to 10k users is not just a function of building good software its also basically going to need you to be a part time salesperson/marketer which feels annoying/I dont enjoy it My main motivation to build a project is to get more interviews

I am confident about cracking interviews, but the issue is that I'm not receiving any interview invitations. I successfully interviewed for a Data Science role in Supply Chain and was converted to full-time. However, since then, I haven't secured any interviews. I've attempted to apply with referrals Links, but no luck. Could you please review my resume and provide suggestions for improvement? Additionally, do you have any tips on how to secure more interviews? My usual process involves going to LinkedIn, identifying a suitable job, connecting with many people in similar roles at that company, and requesting a referral before applying for the role. This is my resume -

I am trying apply to companies via referrals by reaching out to people on LinkedIn who work there already. Some people give me a yes but never get back after that. I understand that it's a transaction, but I don't know what value i could offer them in return for a referral? Or how I could get them interested in referring me? Any tips? Thanks!

I graduated University of Toronto computer science (ranked by ARWU as 1st in Canada and 9th in the world) with a decent GPA around a year ago. Following graduation, I applied to hundreds of jobs, networked aggressively, and skilled up as much as possible for around three months straight, every day, for the entire day. I landed a ridiculously small number of interviews, and I ended up landing a low-paying dev job with a stack I did not want in a tiny company with no employee benefits. Not exactly the tech bro dream 🥲. Comparing with many of my peers who have similar backgrounds to me and who landed great jobs straight out of college, it's hard for me to know whether I'm falling victim to LinkedIn survivorship bias (i.e. I'm only seeing those who succeed) or if I am missing something here. Perhaps it's that I didn't do any internships during college, or that the market is bad right now, or that one simply needs referrals to get interviews. I am hoping to gain clarity on this. My formal questions: I am a graduate of one of the top computer science programs in North America, have a decent GPA, and have a portfolio of college projects. It's hard for me to assume my resume is that suboptimal that it undoes those facts. Why are companies not interested in interviewing me? I have two years of experience total at two different companies, both of which are very small consultancies owned by friends of friends, which I suspect may be hurting my application. Is it better to apply for recent grad jobs or internships (which I'm applying for anyway) with no professional experience listed on my resume? Something that I've seen emphasized on Taro is that it is much more attractive to specialize. For example, in the resume course, Alex recommends applying with a small number of technologies you are proficient in / have experience with. As a recent grad not getting interviews, I am (a) nervous I'll get thrown into a tech stack I don't care for, but thereafter only have a real chance at success interviewing for jobs with that stack, and (b) not actually proficient with any tech stack, so not sure I can craft a "specialized" resume. What are your thoughts on this, and what does a strong recent grad resume look like? Thank you very much for taking the time to answer and for Taro's support in the job search!

I have always thought like its impossible to get into FAANG companies, and when I got it, I felt also the imposter syndrome. Now after sometime there, I look back and try to think about reasons that could prevent us from applying, I think mine was just thinking that I will not make it anyway, although now ai know I was mistaken. What about you. What is your reason?

Can you share resources for data-related interviews (applied data science, data analysis, sql, big data, etc). Also, any tips that a former software engineer can best prepare for switching roles to a data engineer.

I had an interview with a 60 person company last week. It was the first round with the Hiring Manager. It went well and he told me he'd move me on to the next round. It's been 6 days and I haven't heard back from the company. I'm wondering if I should ping the recruiter, but here's the thing: I don't necessarily want to have my next interview soon because I have other companies I'm speaking with. So this question has 2 parts: Assuming I want to interview with the company sooner rather than later so I can get an offer (fingers-crossed) sooner rather than later, has enough time gone by to warrant me pinging the recruiter? If I don't want to get an offer sooner, but instead am fine getting an offer later, should I still reach out? I suppose you can separate reaching out for when you schedule the interview for, although they're definitely generally correlated.

I'm a Data Engineer. Within the data engineering realm, there are a lot of tools, just like in the software engineering realm. The modern data stack is pretty popular these days. It includes things like Spark for ETL at scale, Docker for virtualized environments, Airflow for orchestration, dbt (data build tool) for transformations in SQL, Fivetran for automated data connectors, Snowflake for data warehousing, and more. I'm far from knowing all of these tools well, primarily because I use very few of them in my day job. The main reason I want to change jobs is because of this. I'm worried I'm caught in a catch-22 situation where I don't know the tools so I can't get jobs that have them, which I guess is similar to the new-grad cold start problem. My question is, how should I think about learning new tools for job interviews? My current instinct is to learn via failure. That is, I have almost all of the above tools on my resume. If someone asks me about them and I'm not able to give a good answer, I will learn that part about the tool so if I'm in the same situation I can answer properly. Another approach I can think of is to do Udemy courses of them so I have a deeper understanding of how they work. I've learned to be wary of course not tied to projects, though, so I'm hesitant. I guess I could do projects to learn more about them, but those take time and right now I'm focused on applying to jobs. I imagine some answers might focus on what my current problem is: can I get interviews or am I failing interviews? I don't think my issue is with failing interviews right now, and certainly not because of specific knowledge people have called me out for for not knowing these tools. I think my issue is more with sourcing interviews currently. If there's general advice regarding how to think about prepping for an interview when you only have some of the requirements on the Job Description, would love to hear that too. Thanks!

Hi There, I am based in the UK and have been offered a staff computer vision engineer position at a growth-stage startup. The offer has already been finalized, but the company's CTO has requested my previous employer's recent payslip. This is unusual in my experience, as no one has ever asked for my payslips before. I initially thought they might use the payslip to determine my compensation, but that has already been decided and communicated to me. I negotiated a signing bonus based on my expected salary expectations and a "made-up current salary (range )" because the base salary offered was not appropriate for the market rate. During the interview process, I mentioned my current salary, which was not the exact real number (as per Rahul's advice). However, now that they are asking for my payslip, it will reveal my actual salary. I am concerned that this might leave a bad impression and create trust issues with the CTO, potentially affecting our working dynamics. I love the team and the project, and everything else seems promising. However, I am unsure about how to proceed with this situation. The recruiter mentioned that the payslip is required for administrative purposes, but I am still hesitant. Any advice on how to handle this would be greatly appreciated.