# Software Engineer
**Role:** Software Engineer · **Level:** L7
**Company:** [Verily](https://scaleengineer.com/companies/verily)
**Difficulty:** Hard
**Salary:** US$180000 - US$250000
**Experience:** 8 - 15
**Timeline:** ~4 days
Verily's L7 Software Engineer interview process is designed to assess a candidate's deep technical expertise, problem-solving abilities, system design skills, and leadership potential. The process is rigorous and aims to identify individuals who can drive complex projects, mentor junior engineers, and contribute significantly to Verily's innovative environment.
Canonical: https://scaleengineer.com/interviews/verily/l7-software-engineer
---
## Overall evaluation

- Technical Proficiency
- System Design & Architecture
- Problem Solving & Analytical Skills
- Behavioral & Leadership
- Cultural Fit & Motivation

## Questions asked

- Design a system to manage patient health records, ensuring privacy and scalability.
- How would you optimize a data pipeline processing millions of genomic sequences daily?
- Describe a time you disagreed with a technical decision made by your team lead. How did you handle it?
- What are the trade-offs between using a relational database and a NoSQL database for storing time-series biological data?
- How do you approach mentoring junior engineers and fostering a collaborative team environment?
- Imagine you need to build a real-time anomaly detection system for sensor data. Outline your approach.
- Tell me about a challenging bug you encountered and how you debugged it.
- How do you ensure the quality and reliability of software in a fast-paced environment?
- What are your thoughts on microservices vs. monolithic architectures in the context of health tech?
- Describe a situation where you had to influence stakeholders to adopt a new technical direction.

## Preparation tips

### lists

- Review fundamental computer science concepts: data structures, algorithms, operating systems, databases.
- Practice system design problems, focusing on scalability, reliability, and trade-offs.
- Prepare behavioral questions using the STAR method (Situation, Task, Action, Result).
- Research Verily's mission, products, and recent news to understand their business and technical challenges.
- Brush up on your preferred programming languages and be ready to write clean, efficient code.
- Understand distributed systems concepts like consensus, replication, and fault tolerance.
- Prepare to discuss your past projects in detail, highlighting your contributions and technical decisions.
- Consider practicing mock interviews with peers or mentors.

### studyPlan

- {"title":"Data Structures and Algorithms","longDescription":"Weeks 1-2: Focus on core data structures (arrays, linked lists, trees, graphs, hash tables) and algorithms (sorting, searching, dynamic programming, graph traversal). Practice implementing these in your primary language and analyze their time/space complexity. Solve LeetCode problems tagged 'Medium' and 'Hard'.","shortDescription":"Weeks 1-2: Data Structures & Algorithms (LeetCode Medium/Hard)"}
- {"title":"System Design","longDescription":"Weeks 3-4: Dive into system design principles. Study topics like load balancing, caching, database scaling (SQL vs. NoSQL), message queues, microservices architecture, and CAP theorem. Review common system design interview questions and practice designing systems like Twitter feed, URL shortener, or a distributed cache.","shortDescription":"Weeks 3-4: System Design Fundamentals & Practice"}
- {"title":"Behavioral Preparation","longDescription":"Week 5: Prepare for behavioral questions. Reflect on your career experiences and identify examples that demonstrate leadership, teamwork, problem-solving, and conflict resolution. Use the STAR method to structure your answers. Research Verily's values and prepare to align your experiences with them.","shortDescription":"Week 5: Behavioral Preparation (STAR Method)"}
- {"title":"Technology & Mock Interviews","longDescription":"Week 6: Focus on specific technologies relevant to Verily, such as cloud platforms (GCP/AWS), big data technologies (Spark, Hadoop), and potentially machine learning frameworks. Review your resume and be ready to discuss any project in depth. Conduct mock interviews to simulate the actual interview environment.","shortDescription":"Week 6: Technology Deep Dive & Mock Interviews"}

## Location differences

- {"location":"San Francisco Bay Area","differences":{"tips":["Familiarize yourself with common cloud platforms (GCP, AWS) and their services relevant to data science and machine learning.","Prepare to discuss specific examples of leading technical projects and mentoring junior engineers.","Research Verily's current projects and technologies to tailor your answers.","Be ready to articulate your understanding of scalability, fault tolerance, and performance optimization in large-scale systems."],"interviewFocus":["Emphasis on practical application of advanced algorithms and data structures in biological contexts.","Deeper dive into distributed systems and cloud-native architectures relevant to large-scale data analysis.","Assessment of leadership and mentorship capabilities in driving technical initiatives.","Understanding of regulatory compliance and data privacy in healthcare/life sciences."],"commonQuestions":["Discuss a time you had to influence a team to adopt a new technology. What was the outcome?","Describe a complex technical challenge you faced in a distributed system and how you resolved it.","How do you approach designing a scalable and reliable data processing pipeline for biological data?","Tell me about a project where you had to make significant architectural decisions. What was your thought process?","How do you stay updated with the latest advancements in software engineering and their potential application at Verily?"]}}
- {"location":"Boston","differences":{"tips":["Highlight experience with bioinformatics tools and libraries if applicable.","Be prepared to discuss your contributions to open-source projects or significant internal tooling.","Showcase your ability to communicate complex technical concepts to non-technical stakeholders.","Emphasize your problem-solving methodology and how you approach ambiguity."],"interviewFocus":["Focus on experience with large-scale data processing and analytics, particularly in genomics or bioinformatics.","Evaluation of expertise in building and maintaining robust, high-performance systems.","Assessment of ability to collaborate effectively with cross-functional teams (e.g., biologists, data scientists).","Understanding of software development best practices and CI/CD pipelines."],"commonQuestions":["How would you design a system to handle real-time genomic data analysis?","Describe a situation where you had to debug a critical production issue in a complex system. What was your approach?","What are your strategies for ensuring code quality and maintainability in a large codebase?","How do you balance technical debt with delivering new features under tight deadlines?","Discuss your experience with machine learning model deployment and monitoring in a production environment."]}}

## Round 1: Technical Coding Round 1
**Type:** Data Structures and Algorithms Interview · **Difficulty:** Hard · **Duration:** 60 min
Assess core CS fundamentals through coding challenges.
This round focuses on your fundamental computer science knowledge. You will be asked to solve 1-2 algorithmic problems, typically involving data structures like trees, graphs, or hash maps, and algorithms such as dynamic programming or graph traversal. The interviewer will assess your ability to write clean, efficient code and explain your thought process clearly. Expect questions that require optimizing solutions for time and space complexity.
**Interviewers look for:** Strong grasp of data structures and algorithms.; Clean, well-structured, and efficient code.; Logical and systematic approach to problem-solving.; Ability to explain trade-offs and justify choices.
**Evaluation criteria:** Correctness and efficiency of algorithmic solutions.; Understanding of time and space complexity.; Coding proficiency and clarity.; Ability to communicate the solution and thought process.
**Common rejection reasons:** Inability to articulate thought process clearly.; Lack of depth in understanding fundamental algorithms.; Poorly optimized code or incorrect solutions.; Failure to consider edge cases and constraints.
## Questions

- Given a binary tree, find the lowest common ancestor of two given nodes.
- Implement a function to find the k-th largest element in an unsorted array.
- Design and implement a data structure that supports insertion, deletion, and getRandom O(1) operations.

## Preparation tips

- Practice coding problems on platforms like LeetCode, focusing on medium and hard difficulties.
- Review common algorithms and data structures.
- Practice explaining your thought process out loud while coding.
- Be prepared to discuss the time and space complexity of your solutions.

## Round 2: System Design Round
**Type:** System Design Interview · **Difficulty:** Hard · **Duration:** 60 min
Assess ability to design scalable and reliable distributed systems.
This round evaluates your ability to design large-scale, distributed systems. You'll be presented with a high-level problem (e.g., design a URL shortener, a social media feed, or a ride-sharing service) and expected to outline a system architecture. Focus on scalability, reliability, availability, and trade-offs. Discuss database choices, caching strategies, load balancing, and API design.
**Interviewers look for:** Ability to design complex, distributed systems.; Deep understanding of system components and their interactions.; Pragmatic approach to problem-solving, considering real-world constraints.; Clear communication of design rationale and trade-offs.
**Evaluation criteria:** Scalability and performance of the proposed system.; Reliability, fault tolerance, and availability.; Clarity and justification of design decisions.; Consideration of trade-offs (e.g., consistency vs. availability).; Understanding of various system components (databases, caches, load balancers, etc.).
**Common rejection reasons:** Inability to design a scalable and robust system.; Overlooking critical components like error handling, monitoring, or security.; Lack of clarity in explaining design choices and trade-offs.; Not considering different user loads or failure scenarios.
## Questions

- Design a system like Google Maps.
- Design a notification service for a large-scale application.
- Design a distributed key-value store.

## Preparation tips

- Study common system design patterns and architectures.
- Practice designing various systems, considering different requirements.
- Be prepared to discuss trade-offs for each design choice.
- Think about potential bottlenecks and how to address them.
- Familiarize yourself with cloud services and their roles in system design.

## Round 3: Managerial / Behavioral Round
**Type:** Behavioral and Leadership Interview · **Difficulty:** Hard · **Duration:** 45 min
Assess behavioral traits, leadership, and cultural fit.
This round, often conducted by the hiring manager, focuses on your behavioral and leadership qualities. You'll be asked questions about your past experiences, focusing on how you've handled challenges, worked in teams, led projects, and dealt with conflict. Prepare to provide specific examples using the STAR method. The interviewer will also assess your motivation for joining Verily and your understanding of the role.
**Interviewers look for:** Evidence of leadership and impact.; Ability to handle complex and ambiguous situations.; Strong communication and interpersonal skills.; Proactive approach to problem-solving and continuous learning.; Alignment with Verily's mission and values.
**Evaluation criteria:** Problem-solving skills and analytical thinking.; Communication and collaboration abilities.; Leadership potential and experience.; Behavioral competencies (e.g., handling conflict, dealing with ambiguity).; Alignment with Verily's culture and values.
**Common rejection reasons:** Lack of clear communication or inability to articulate thought process.; Poor problem-solving approach or inability to break down complex issues.; Lack of ownership or accountability for past projects.; Inability to demonstrate leadership or mentorship qualities.; Poor cultural fit or lack of alignment with Verily's values.
## Questions

- Tell me about a time you had to lead a project from conception to completion. What were the biggest challenges?
- Describe a situation where you had to deal with a difficult team member. How did you resolve it?
- How do you stay motivated when working on long-term, complex projects?

## Preparation tips

- Prepare specific examples using the STAR method for common behavioral questions.
- Reflect on your leadership experiences and impact.
- Research Verily's mission, values, and culture.
- Think about why you are interested in this specific role and company.
- Prepare thoughtful questions to ask the interviewer.

## Round 4: Specialized Technical Round
**Type:** Technical Deep Dive / Pair Programming · **Difficulty:** Hard · **Duration:** 60 min
Assess specialized technical skills and collaborative problem-solving.
This round might involve a deeper dive into a specific technical area relevant to the team you're interviewing for, or it could be a pair programming session. The interviewer will assess your expertise in areas like distributed systems, cloud technologies, specific programming languages, or machine learning, depending on the team's focus. The goal is to understand how you approach real-world technical challenges and collaborate with others.
**Interviewers look for:** Expertise in areas critical to the team's work.; Ability to work collaboratively and contribute to team success.; Practical application of technical skills.; Enthusiasm and passion for the domain.
**Evaluation criteria:** Depth of knowledge in specialized areas (e.g., distributed systems, machine learning, specific programming languages).; Ability to collaborate effectively on technical problems.; Problem-solving skills in a practical, hands-on context.; Communication of technical ideas and solutions.
**Common rejection reasons:** Lack of deep technical expertise in a specific domain relevant to the team.; Inability to articulate complex technical concepts clearly.; Poor collaboration or communication during a pair programming session.; Not demonstrating sufficient ownership or initiative.
## Questions

- Let's discuss your experience with building and deploying machine learning models at scale. What challenges did you face?
- We need to design a real-time data processing pipeline for sensor data. How would you approach this, considering latency and throughput?
- Pair programming: Implement a rate limiter for an API.

## Preparation tips

- Understand the specific technologies and domains relevant to the team you are interviewing with.
- Be prepared to discuss your experience with specific tools and frameworks in detail.
- Practice collaborative coding if the round involves pair programming.
- Think about how your skills align with the team's current projects and challenges.