Scale Engineer

Software Engineer

Software EngineerSenior Staff SWEHard

Moloco is seeking a Senior Staff Software Engineer with a strong background in distributed systems, algorithms, and problem-solving. This role involves designing, developing, and scaling high-performance, low-latency systems that power Moloco's advertising technology platform. The ideal candidate will have a proven track record of technical leadership, mentoring junior engineers, and driving complex projects to completion.

Rounds·5

Timeline·~14d

Experience·8 - 15 yrs

Comp band·US$180000 - US$250000

Interview time·225 min

Evaluation

What they measure.

  • Problem-solving ability: Ability to analyze complex problems, identify root causes, and propose effective solutions.
  • System Design: Ability to design scalable, reliable, and maintainable distributed systems, considering trade-offs and best practices.
  • Technical Depth: Deep understanding of computer science fundamentals, algorithms, data structures, and distributed systems concepts.
  • Coding Proficiency: Ability to write clean, efficient, and well-tested code.
  • Communication Skills: Ability to articulate technical ideas clearly and concisely, both verbally and in writing.
  • Leadership and Mentorship: Ability to guide and mentor junior engineers, influence technical decisions, and drive projects forward.
  • Cultural Fit: Alignment with Moloco's values, including collaboration, innovation, and a focus on impact.

Preparation

How to prepare.

Tips

  1. Review fundamental computer science concepts: data structures (arrays, linked lists, trees, graphs, hash tables), algorithms (sorting, searching, graph traversal, dynamic programming), and complexity analysis (Big O notation).
  2. Deep dive into distributed systems concepts: CAP theorem, consistency models (strong, eventual), consensus algorithms (Paxos, Raft), distributed transactions, message queues, caching strategies, load balancing, and fault tolerance.
  3. Practice system design problems: Focus on designing scalable, high-availability systems for common scenarios like social media feeds, URL shorteners, chat applications, and ad tech platforms.
  4. Brush up on your coding skills: Practice coding problems on platforms like LeetCode, HackerRank, or Coderbyte, focusing on medium to hard difficulty problems, especially those related to algorithms and data structures.
  5. Understand Moloco's business and technology: Research Moloco's products, services, and the challenges in the ad tech industry. Think about how your skills can contribute to our success.
  6. Prepare for behavioral questions: Reflect on your past experiences and prepare examples that demonstrate your leadership, problem-solving, collaboration, and conflict-resolution skills using the STAR method (Situation, Task, Action, Result).
  7. Mock interviews: Conduct mock interviews with peers or mentors to simulate the interview environment and get feedback on your performance.

Study plan

Fig · Study plan — 05 phases

01 / 05
01

Phase 01 of 05

Data Structures and Algorithms

Weeks 1-2: Data Structures & Algorithms (LeetCode Medium/Hard).

Weeks 1-2: Focus on core data structures and algorithms. Cover arrays, linked lists, stacks, queues, trees (binary search trees, AVL trees, B-trees), heaps, hash tables, and graphs. Study sorting algorithms (quicksort, mergesort), searching algorithms (binary search), graph traversal (BFS, DFS), and dynamic programming. Practice implementing these structures and algorithms and analyzing their time and space complexity. Aim for 1-2 LeetCode medium problems per day.

Questions

Commonly asked.

  • Design a distributed caching system for a global ad platform.
  • Describe a challenging debugging scenario you faced in a production environment and how you resolved it.
  • Discuss the trade-offs between different consensus algorithms (e.g., Paxos, Raft) in the context of our services.
  • How do you approach performance optimization for high-throughput, low-latency services?
  • What are your strategies for ensuring data consistency in a distributed system with eventual consistency guarantees?
  • Explain the principles of chaos engineering and how you might apply them to our infrastructure.
  • How do you mentor and guide junior engineers on complex technical challenges?
  • Describe a time you had to influence a technical decision across multiple teams.
  • What are your thoughts on the future of machine learning in ad tech, and how can we leverage it more effectively?
  • How do you balance technical debt with the need for rapid feature development?

Locations

Regional differences.

Fig · Regions — 03 locations

01 / 03

Location

USA

Interview focus

Deep understanding of distributed systems architecture and trade-offs.Ability to design for scale, reliability, and performance under heavy load.Strong problem-solving and debugging skills in complex, distributed environments.Leadership potential and experience in mentoring and technical guidance.Strategic thinking about system design and future scalability.Communication and collaboration skills to influence technical direction.

Common questions

  • How would you design a distributed caching system for a global ad platform?
  • Describe a challenging debugging scenario you faced in a production environment and how you resolved it.
  • Discuss the trade-offs between different consensus algorithms (e.g., Paxos, Raft) in the context of our services.
  • How do you approach performance optimization for high-throughput, low-latency services?
  • What are your strategies for ensuring data consistency in a distributed system with eventual consistency guarantees?
  • Explain the principles of chaos engineering and how you might apply them to our infrastructure.
  • How do you mentor and guide junior engineers on complex technical challenges?
  • Describe a time you had to influence a technical decision across multiple teams.
  • What are your thoughts on the future of machine learning in ad tech, and how can we leverage it more effectively?
  • How do you balance technical debt with the need for rapid feature development?

Tips

  • For US-based interviews, expect a strong emphasis on system design for large-scale, real-time bidding systems. Be prepared to discuss latency optimization and fault tolerance in detail.
  • For European-based interviews, while system design is crucial, there might be a slightly higher emphasis on practical implementation details and code quality. Familiarize yourself with common European tech stacks and best practices.
  • For Asia-based interviews, expect a rigorous approach to algorithmic problem-solving and data structures, alongside system design. Be ready to discuss your experience with large datasets and high-concurrency systems.
  • Regardless of location, demonstrate a clear understanding of Moloco's business and how your technical contributions impact our success.

Rounds

Round-by-round.

Expand a step for evaluation criteria, sample questions, and prep notes.

DSA

Coding questions at Moloco.

Frequently reported on Moloco loops

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Other guides

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