Round Structure ML System Design

In this segment, we’re introduced to one of the most critical and career-defining parts of the ML interview process: **system design**. Especially at senior and staff levels, this round reveals our ability to lead and think holistically.

- **System design interviews evaluate both breadth and depth**—we’re expected to understand the full ML pipeline from data ingestion to deployment and monitoring.
- This round is less about solving isolated problems and more about **architecting end-to-end solutions** that operate under real-world constraints.
- We must demonstrate our ability to **make trade-offs** involving scalability, latency, noisy data, evolving product requirements, and long-term maintenance.
- Strong performance here often **distinguishes mid-level candidates from senior or leadership-level hires**.
- Ultimately, it’s our chance to show that we can **design ML systems that work, scale, and deliver value in production—not just in theory**.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

Amazon Behavioral Interview [Part 27] - Recovering From A Bad Decision (Answer)

This video segment describes a situation where the interviewee made a mistake in their role at American Express.

- **Identified the Mistake:** The interviewee implemented a new incentive system for customer care professionals that rewarded them for saving high-value customers while neglecting lower-value customers. This led to:

  - **Cherry-picking of customers:** Customer care professionals prioritized high-value customers, leading to long wait times for lower-value customers.
  - **Negative customer experience:** Long wait times resulted in poor customer satisfaction and potentially damaged brand reputation.
  - **Missed revenue opportunities:** Neglecting lower-value customers, particularly early-tenure customers, resulted in missed opportunities for future revenue growth.

- **Learned from the Mistake:** The interviewee learned the importance of:

  - **Considering all stakeholders:** Involving customer care professionals in the decision-making process.
  - **Thinking long-term:** Considering the long-term value of customers, not just their immediate spending.
  - **Gathering diverse perspectives:** Seeking input from former team members to identify potential pitfalls.

- **Implemented Corrective Actions:**

  - Revised the incentive system to account for customer lifetime value.
  - Implemented measures to improve call center response times and reduce wait times.
  - Developed a system to identify and address cases of long wait times for customers.

This example demonstrates the interviewee's: 

- ***Self-awareness:*** *Acknowledging and taking responsibility for their mistake.* 
- **Problem-solving skills:** Identifying the root cause of the issue and implementing corrective actions. 
- ***Learning agility:*** *Learning from the mistake and applying those learnings to future projects.* 
- **Focus on customer experience:** Prioritizing customer satisfaction and long-term customer relationships. 
- **Continuous improvement:** Continuously refining processes and seeking ways to improve performance.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

How Managers Hire Great Engineers [Part 17] - Push & Pull Factors

It's hard convincing great engineers to leave their current jobs. From this lesson, you will:

- Understand the importance of increasing your candidate acceptance rate, which can significantly reduce workload throughout the recruitment funnel
- Learn how to identify and leverage push and pull factors that influence a candidate's decision to leave their current role or join your company
- Discover the value of tailoring your closing approach to individual candidate motivations to enhance offer acceptance rates
- Gain insights into conducting honest Q&A sessions during the closing call to ensure a good fit, thereby increasing long-term retention on your team

Connect with John Egan on LinkedIn: <https://www.linkedin.com/in/jwegan/>

In this segment, we explore the importance of **Exploratory Data Analysis (EDA)** in machine learning interviews, especially during notebook-based exercises. This is a key moment to distinguish ourselves by demonstrating analytical depth and real-world intuition.

- We move beyond just **checking for missing values or printing basic stats**, which signals a surface-level approach.
- Instead, we analyze **feature distributions**, identifying skewness, outliers, and unusual patterns that may affect modeling.
- We examine **relationships and interactions between variables**, not just computing correlations, but exploring potential dependencies and dynamics.
- We assess **data quality**, including duplicates, inconsistent categorical values, and signs of data leakage.
- This deeper EDA shows that we can **interrogate the data critically**, a trait that interviewers associate with strong, production-ready ML practitioners.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

Become An Engineer Influencer [Part 10] - Story-Telling

Become An Engineer Influencer [Part 7] - Mid-Funnel Channels

Just A Cog In The Machine

Although Big Tech offers compensation and prestige, the sheer scale of these organizations can lead engineers to feel like small cogs in an enormous machine. The work often becomes highly specialized and incremental, making it harder to find personal fulfillment or a sense of ownership.

- **Incremental Work Dominates**: Many engineers are tasked with refining already hyper-optimized features, such as tweaking a single call-to-action button on an ad format. This kind of work can feel repetitive and lacking in creative fulfillment.
- **Limited Ownership**: As teams grow larger, individual engineers may end up owning only a sliver of a product component—sometimes just one platform’s implementation of a single UI element.
- **Slower Innovation in Mature Products**: Legacy systems and products that have been around for over a decade (like Gmail) may offer fewer opportunities for impactful changes, making it harder to grow scope or gain recognition.
- **High Competition for Scope**: Even when surrounded by brilliant engineers, opportunities for meaningful ownership can be scarce. This leads to competition over small improvements and sometimes a struggle to stand out.
- **Pockets of Growth Still Exist**: Certain high-growth teams such as those working on newer initiatives like AI or experimental products can still offer dynamic, zero-to-one opportunities. Success often depends on finding and joining these pockets within the broader organization.

Become An Engineer Influencer [Part 14] - Tips on Writing

He Bought Coffee For ALL Meta Employees On His Last Day

Philip's Biggest Concern: The Future Of Work

Ship & Grow 500k+ User Side Projects [Part 20] - When To Give Up

Side projects can give you massive, career-changing, *life-changing* benefits. However, in order for this to happen, you need to put in a lot of work. This lesson teaches you:

- The balance you need to strike when it comes to working on side projects, particularly which ones you work on
- The minimum amount of time you need to give a side project that you genuinely believe in
- A detailed list of criteria you can use to figure out whether you should abandon a side project
- Why failed side projects are actually good for you

"What is the growth plan for Taro Premium?" - 8/18/2022

There are 2 core areas at play here:
1. Empowering Taro Premium members to share their diverse wealth of perspectives and wisdom
2. Tactical areas of improvement

**Communal Sharing**
- Right now, Rahul and I are doing the thing that doesn't scale in true startup fashion: Providing the vast majority of career guidance ourselves.
- However, not only does this not scale, we firmly believe that this isn't the right thing to do long term: Our perspectives are only 2 out of millions of incredible people working in tech.
- Let me be frank: While we've had a diverse range of experience and pushed to understand as many angles of the tech scene as possible, our perspective is narrow. We've only worked in the Silicon Valley. We're around the same age. We spent the lion's share of our careers working at Meta. We're both Asian men. Because of this, there's a lot of stuff we don't know and aren't well equipped to talk about.
- This is where the community comes in. At the time of release of this video, we have ~170 members in Taro Premium, and I've been blown away by the diversity of backgrounds present. If we can enable, reward, and empower all these incredible folks in tech to share their perspectives and help one another, we can create what is truly the greatest repository of tech career advice on Earth.

**Tactical Stuff**
- Our main priority right now is opening up the Q&A career advice platform, so that all members of Taro Premium can easily ask and answer questions.
- While this was recently made possible, there's still a lot lacking. There's no notifications to know when your question has been answered, and we all know that the UI/UX has a ton of room for improvement, especially on web.
- We're working with a contract designer right now to completely overhaul the look and feel of the Taro web app.
- Another thing we want to figure out is member matching. For now, we're mainly matching folks of similar level as the incentives get wonky when you pair folks of different levels. However, this "algorithm" is still quite naive, and we have a long way to go before we can sustainably have folks network with one another in a way where all parties feel like they got value.

Paper Reading - Gemini: A Family of Highly Capable Multimodal Models

Paper Discussion led by: [Akshika Wijesundara PhD](https://www.linkedin.com/in/akshika/)

Abstract: Google researchers recently unveiled Gemini, a ground breaking family of multimodal AI models capable of understanding and reasoning across images, audio, video, and text. The largest Gemini model, Ultra, achieved human-expert performance on several benchmarks and advanced the state of the art across a range of multimodal tasks.

In this paper reading, we will discuss key details from Google's paper introducing Gemini models. Topics will include:

- The Gemini model architectures and how they achieve cross-modal understanding
- Performance benchmarks and state-of-the-art results across text, image, audio, and video tasks
- Applications and use cases enabled by Gemini's multimodal reasoning
- Approaches to responsible deployment of large language models like Gemini

This paper provides a comprehensive overview of the exciting new capabilities of Google's Gemini project. Whether you're an AI researcher, engineer, or simply curious about the state of the art in multimodal AI, join us for an in-depth look at this new model family.\
\
Paper link: [**https://arxiv.org/abs/2312.11805**](https://arxiv.org/abs/2312.11805)\
Event link:  **[https://www.jointaro.com/event/paper-reading-gemini-a-family-of-highly-capable-multimodal-models/](https://www.jointaro.com/event/paper-reading-gemini-a-family-of-highly-capable-multimodal-models/)**

Can A Company Demand High Performance AND Allow Learning?

How Managers Hire Great Engineers [Part 11] - Meetups and Conferences

When it comes to relationship building, you simply cannot beat in-person interaction. From this lesson, you will:

- Understand the value of making personal connections at meetups and conferences to stand out from the noise of digital outreach
- Learn strategies for building a network by engaging with people at events, collecting their contact information for future outreach
- Discover how creating and hosting your own events can establish your brand as a company and attract potential candidates
- Realize the benefits of long-term recruitment through sustained relationships with event attendees and speakers
- Explore how relationships with speakers at your events can evolve into hiring opportunities for top talent in the future

Connect with John Egan on LinkedIn: <https://www.linkedin.com/in/jwegan/>

Taro Book Club: Designing Data Intensive Applications - Chapter 3

Topic: Chapter 3 - Storage and Retrieval

In this #taro-bookclub discussion, we talk about Chapter 3 of [**"Designing Data-Intensive Applications"**](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321) by Martin Kleppmann.

Here's the agenda:

- Let’s get to know each other with some quick introductions.
- We’ll break down and discuss the key concepts from Chapter 3.
- There will also be time for any questions and answers you might have.

Thanks to [**Suraj Singh**](https://www.linkedin.com/in/suraj-singh-495b192b/) and [**Sangavi Pari**](https://www.linkedin.com/in/sangavi-pari/) for leading this session!

Maximize Your Equity And Benefits In Tech [Part 17] - 401(k) And IRA Basics

Understanding retirement accounts is essential for long-term financial planning. Here’s the core points from the lesson:

- 401(k)s allow automated payroll contributions (up to $23,500 in 2025 for those under 50), often include employer matching, and offer pre-tax or Roth contribution options
- Contributions reduce taxable income but are still subject to payroll taxes like Social Security and Medicare
- IRAs (individual retirement arrangements) are similar to 401(k)s but are personally managed, have lower contribution limits, and don’t include employer matching
- IRA contributions may be tax-deductible or Roth-eligible depending on your income, unlike 401(k)s which have no income-based restrictions for pre-tax contributions

Next steps with Andy:

- [Connect with Andy on LinkedIn](https://www.linkedin.com/in/andymoranio)
- [Leave feedback and/or sign up for Andy’s newsletter](https://subscribepage.io/taroequitycourse)
- [Schedule a consultation](http://adastrafp.com/contact-us/)

Well Roundedness

Working in Big Tech expands far beyond engineering; it shapes individuals into well-rounded professionals by pushing them to develop skills in communication, leadership, and cross-functional collaboration.

- **Development of cross-functional skills**: Navigating product launches or technical changes in a large organization requires coordination across many stakeholders, honing project management, communication, relationship-building, and system design abilities.
- **Environment fosters personal growth**: Operating within a large, complex structure forces individuals to adapt, influence, and lead through collaboration—skills less emphasized in smaller, more agile companies.
- **Preparation for an AI-driven future**: As coding becomes more automated, the remaining 80% of a top engineer’s job like communication, strategy, and leadership becomes even more valuable. This environment equips engineers for longevity in their careers.
- **Transferable experience for career switchers**: Even those new to tech can succeed by leveraging skills from prior careers (e.g., hospitality, education, operations). Communication and stakeholder management experience, in particular, translate well.
- **Resilience through versatility**: Focusing on foundational skills that transcend tech stacks or tools creates career durability, avoiding dependency on niche or outdated technologies.

Taking Things Further

In Part 4 of the course, we focus on how to **embed "thinking in deltas" as a daily leadership habit**. This final module emphasizes how to continuously spot and create positive, sustainable change as a manager—not just react to problems.

- **We build the habit by journaling our daily deltas**, capturing the tangible changes we influence, however small.
- **We use the journal to reframe how we think**, making it easier over time to spot opportunities for impact in individuals, teams, and systems.
- **We improve our mental well-being as managers** by recognizing our contributions and wins in a role where feedback loops are long and ambiguous.
- **We measure our success not just by outputs, but by meaningful changes we've catalyzed**—deltas we can point to as outcomes of our leadership.

Creating a daily "delta journal" isn’t just about reflection—it’s how we grow our impact and resilience as leaders.

If you want to learn more from Gilad, he shares free leadership advice daily on [LinkedIn](https://www.linkedin.com/in/giladnaor/?utm_source=taro&utm_medium=course&utm_campaign=cta) and weekly on the[ δeltas newsletter](https://posts.managementdeltas.com/?utm_source=taro&utm_medium=course&utm_campaign=cta)

Ship & Grow 500k+ User Side Projects [Part 9] - Leverage Existing Patterns

Just because you're an engineer doesn't mean that you can't be a solid product designer. This lesson teaches you:

- The easiest way to bootstrap a product design from scratch
- What the pinnacle of front-end UI/UX looks like and the company behind it
- A company you can use as inspiration for a back-end project
- A company you can use as inspiration for an ML project

Tech Career Growth Videos

Our instructional videos provide software engineers with insights needed for career growth. Masterclasses go incredibly in-depth on a specific tech topic while case studies are real examples from established engineering leaders.