Candidate had 8 YoE + master’s, Bay Area role, and the package was:

• Base: $230K
• Equity: $845.5K over 4 years (vesting schedule: 40/30/20/10.)
• Annual bonus: $34.5K
• First-year TC: $602.7K

Would you prefer a front-loaded 40/30/20/10 vesting schedule, or a more predictable 25/25/25/25?

At what point does private-company equity start feeling too risky compared with Big Tech RSUs?

And for senior SWE offers, is $600K first-year TC now becoming “top-tier but realistic,” or is this still a rare outlier?

In an email from the CEO this morning

>Hi team,

>We are in extraordinary times and at a pivotal inflection point to shape the future for our customers. Intuit is an iconic company in a category of one with strong market leadership and multiple diversified growth engines serving consumers, businesses, and accountants. We are well positioned to power the prosperity of our customers and create a bright future, but to do so, we must evolve as a company.

>We have significant momentum across our 3 Big Bets and to fully capitalize on this extraordinary opportunity, we need to move with far greater velocity, urgency, and discipline. We must:

>Scale our AI-native platform to deliver easy, done-for-you experiences. We have already built the foundation; now, we must accelerate delivering undisputed customer benefits with an unmatched combination of data, AI, and human expertise.
Be the center of money for consumers and businesses. We will ensure our platform is their primary financial engine, creating a unified ecosystem so our customers can access, manage, and grow their money with confidence.
Accelerate our authority and right to win in the mid-market. We must scale our impact with far greater velocity, becoming the definitive partner for mid-market businesses and accounting firms, and delivering the industry-specific platform they need to manage complexity and scale at the speed of their ambition.

>Shaping the company for the future
Over the past several months, we have spent significant time evaluating how we focus the company with greater velocity and discipline to achieve what I outlined above. We believe we can serve more customers and deliver breakthrough products that fuel our customers’ success by reducing complexity and simplifying our structure to become a faster, leaner, and more focused company. 

>This required us to make a set of difficult decisions that impact our people. Today, we are reducing our full-time workforce by approximately 17%. These are valued colleagues and friends who have been vital to shaping the company we are today. Saying goodbye is never easy, and I want to acknowledge the weight this news carries for all of us.

>Here are the changes we’re making today and why we’re making them:

>Reducing layers of management. We have identified areas where too many organizational layers have slowed the flow of information and hampered our ability to move with speed. By streamlining our leadership structure, we are empowering our teams who are closer to the customer to make decisions, ensuring we operate as a more agile and accountable organization.
Focusing roles on high impact work. As we simplify our structure, we are reducing the need for coordination heavy roles that were previously required to manage the complexity. This allows us to focus our collective energy on mission-critical work that directly impacts our customers' prosperity.
Bringing our teams closer together to accelerate impact. To accelerate the pace of innovation, we are co-locating our teams within strategic hubs to drive deeper collaboration and impact. This includes winding down our Reno and Woodland Hills offices and reducing our presence in other locations. 
Reducing overlap across TurboTax and Credit Karma. With the integration of TurboTax and Credit Karma now largely complete, we are eliminating overlapping and redundant roles to operate as a single, unified team and platform. 
Reallocating resources to our primary growth engines. We are optimizing our business and reducing investments in certain areas, including Mailchimp, and streamlining parts of our engineering and product organizations to better align resources with our 3 Big Bets.

>These changes are a necessary evolution to reduce complexity and architect an organization that operates with the velocity required to fuel our growth engines. We are fundamentally re-engineering our operating model to increase accountability, accelerate decision making, and ensure our execution is as bold as our strategy.

>Taking care of our people
I understand this news is difficult and that you will want to know what this means for you. People who are being impacted will receive a calendar invite by 9:00 AM PT today titled "Discussion about leaving Intuit" to hear from a leader in their organization about their transition.

>I also want to be clear: these decisions are a reflection of our changing structure, not the individuals in these roles. We are parting with talented, dedicated colleagues who have made significant contributions to Intuit and the customers we serve. 

>Our commitment to treating every individual with dignity and respect is a fundamental part of who we are, and it has never been more important than it is right now. To help everyone leaving, we are providing generous support, including:

>Financial*: Employees will receive generous financial support as they navigate this change and identify their next chapter. In the US, employees will receive 16 weeks of base pay, plus 2 additional weeks for every year at Intuit. They will also have a paid transition period, including July RSU vesting and bonus eligibility, before they leave the company with a last day of July 31, 2026. Employees outside the US will receive a country-specific package, based on local requirements.*
Health care*: We will provide at least 6 months of health insurance support to employees who are leaving and enrolled in Intuit medical plans. They will also have access to free mental health support during the transition period and for up to 60 days after leaving Intuit.*
Career*: Each impacted employee will have access to career transition and job placement services. These include resume development, interviewing techniques, and recruiting and job search help.**
Immigration*: For those who need immigration support, the extended transition period will allow individuals on visas extra time to find their next role. Intuit will also provide access to external immigration experts for advice and support at no cost.*

>To those leaving Intuit, thank you. I want to express my deep gratitude for everything you have done for us. Your contributions have shaped who we are today, and the impact you’ve made on our products, our teams, and our customers will endure. You’ve been part of building something meaningful here, and that will never change.

>Looking ahead 
To those of you staying: I know this is a difficult day. Please support one another, and please don’t hesitate to reach out to your manager or the People team if you need anything.

>As we look ahead, this is an incredible inflection point for our customers and Intuit. We have navigated many moments of strategic reinvention over our 40-year history, and once again, we are making the deliberate, hard choices required to ignite higher-velocity progress across our Big Bets and play to win in our core business. Our customers have ambitious goals, as do we. We have a once in a lifetime opportunity and a lot of important work ahead of us to power economic growth for those we serve

>What will carry us forward in this moment is what always has: supporting one another, staying deeply connected to our customers, and moving forward with purpose and determination.

>Sasan

The candidate had a PhD with around 5 YoE, and the package was:

• Base: $300K
• Signing bonus: $100K
• RSU grant: $3M over 4 years
• Annual bonus: $60K
• First-year total comp: $1.21M

Curious what people think: is this a new normal for top ML talent, or just a rare outlier from a company fighting hard for autonomous driving talent?

• Base: $265K
• First-year total comp: $616.5K
• Equity grant: $1.3M over 4 years
• Bonus: $26.5K

Would you take this kind of offer from a fast-growing AI/legal-tech company over a more stable Big Tech senior/staff role?

Just saw a recent Harvey Senior Backend onsite experience, and it’s a good reminder that “simple” coding rounds can still get brutal once edge cases enter the chat.

The onsite was 2 rounds:

Round 1: Text Processing

The candidate was given a sentence and a list of tags, and needed to return the tags that appeared in the sentence as whole-word matches. Matching had to be case-insensitive, and partial matches didn’t count.

At first, this sounds like a basic hash set/tokenization problem: split the sentence, normalize case, strip punctuation, and check each word in O(1).

But then the interviewer extended it to multi-word phrase tags, which changed the problem pretty quickly. Now you need to think about regex, word boundaries, punctuation handling, phrase matching, and avoiding false positives from substring matches.

The candidate said the tricky part wasn’t the core idea, but the string manipulation edge cases.

Round 2: In-Memory File System

The second round was building an in-memory file system from scratch.

Expected features included:

mkdir / directory creation
ls / content listing
write file
read file
append to file
path parsing

The candidate used a generic node class with:

isFile / isDirectory flag
content string
children map: name -> node

Pretty standard trie/tree-style design, but the hard part was getting path traversal and write/append behavior correct under interview pressure.

This offer data point is sourced from chillinterview.com—if you’re negotiating offers, it might be worth checking out.

Saw this LinkedIn Data Scientist offer data point and thought it was pretty interesting for anyone benchmarking DS comp in the Bay Area.

Candidate profile: Master’s, 4 years of experience
Role: Data Scientist, Senior-Level
Location: San Francisco Bay Area
Outcome: Accepted

Comp breakdown:

Base salary: $225,000
Signing bonus: $70,000
RSU grant: $440,000 over 4 years
First-year RSU vest: $110,000
Annual bonus: $22,500
Total first-year comp: $427,500

This interview experience is sourced from chillinterview.com—if you’re prepping on a tight timeline, it might be worth checking out.

Interview Rounds Overview

• Round 1: Coding
• Round 2: Coding
• Round 3: Machine Learning
• Round 4: System Design
• Round 5: Behavioral

Full Details & Solution Approach

I had an onsite interview with LinkedIn for a Machine Learning Engineer role. Here's a breakdown of my experience:

Coding 1: I was given the problem of finding a meeting point for N people standing on a line such that the sum of L1 distances to the meeting point is minimized.

• Follow-up: N houses are located at integer positions. I needed to place K routers (only at house locations) to minimize the L2 distance. Calculating the L2 distance was quite tricky.

Coding 2: I was asked how to estimate a user's rating for a movie given the ratings of n users for m movies. The approach involved using k-NN, and I needed to consider the design of appropriate data structures.

Machine Learning: This round covered standard machine learning fundamentals.

System Design: The task was to design an AI-powered personalized InMail system, focusing on how recruiters can more effectively engage with potential candidates. The round required a complete end-to-end design, including UI considerations.

Behavioral: I was asked project-related questions, but I didn't answer well. I failed to demonstrate the broader impact of my projects. I was told a few days later that they would downgrade the offer to a senior level with a one-year cooling-off period. I asked the recruiter, and the compensation (TC) was around 450k, with equity starting in the second year, which I felt was a bit of a lowball offer.

This interview experience is sourced from chillinterview.com—if you’re prepping on a tight timeline, it might be worth checking out.

>Just saw a recent Meta E5 SWE interview experience focused on AI/ML infrastructure, and it’s a pretty brutal reminder that “doing well” in Big Tech interviews doesn’t always mean an offer.

https://preview.redd.it/h4bqmykrz31h1.png?width=1374&format=png&auto=webp&s=687775a109382ddf916d549daf8d4bc9deef65a3

This offer data point is sourced from chillinterview.com—if you’re negotiating offers, it might be worth checking out.

Someone shared a senior-level AI Research Scientist offer from Thinking Machines Lab in the Bay Area, and the structure is honestly pretty wild.

PhD with 1 YoE, offer accepted:

• Role: AI Research Scientist, Senior-Level
• Location: San Francisco Bay Area
• Base salary: $400,000
• Equity grant: $11,000,000 equity (with 1 year cliff)

This offer data point is sourced from chillinterview.com—if you’re negotiating offers, it might be worth checking out.

Saw an interesting Twilio software engineer offer data point for the Bay Area.

Senior-level SWE, 6 years of experience, bachelor’s degree:

• Base: $208K
• Annual bonus: $26K
• Equity grant: $112K RSUs over 4 years
• Vesting: 25/25/25/25
• First-year total comp: $262K

This coding question is sourced from chillinterview.com—if you’re prepping on a tight timeline, it might be worth checking out.

Design Gym Member Check-In System