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Hudson River Trading·Machine Learning Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

HRT ML Engineer interview with a simulation-style coding problem described verbally, no screen share or written prompt. You have to take good notes because they just talk at you and expect you to reconstruct the problem yourself.

Questions Asked (1)

Q1

N people start at positions on a number line and all move right each time step. A watcher starts at some position and can face left or right, reversing direction at given times. Any person strictly on the side the watcher is facing cannot move that step. After T steps, how many people have reached or passed a target position L? Implement a solution.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The problem was entirely verbal, no written spec, so the first few minutes were just me scribbling and asking clarifying questions to make sure I understood the blocking mechanic.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and assumptions, then propose an efficient simulation or analytical approach. Discuss how to model the watcher's direction changes and the blocking effect, and analyze time complexity. Finally, outline the implementation details and potential optimizations.

Pro tip: Demonstrate strong problem-solving by first walking through a small example to validate your understanding, and mention edge cases like simultaneous events or boundary conditions. This shows attention to detail and robustness, which is crucial in trading systems.

1. Clarify the problem

Ask questions to confirm details: Are positions integers? Do people move simultaneously? How is the watcher's direction determined at each step? What happens if a person is exactly at the watcher's position? This ensures you understand the rules precisely.

2. Model the system

Represent each person's position and movement status. Model the watcher's position and direction over time, noting that direction changes only at given times. Determine how the watcher's facing affects which people can move.

3. Choose an approach

Consider a direct simulation step-by-step, updating positions and handling blocking. For large N or T, explore optimizations like event-based simulation or mathematical analysis of movement patterns.

4. Analyze complexity

Evaluate the time and space complexity of your approach. Discuss trade-offs between simulation and analytical methods, and how to handle large inputs efficiently.

5. Implement and test

Write clean code with clear variable names. Test with small cases, edge cases (e.g., watcher at boundary, all people blocked), and validate against brute force for small inputs.

Key Points to Mention

  • Simultaneous movement and blocking logic: people on the watcher's side cannot move that step.
  • Watcher's direction changes only at specified times, not every step.
  • Efficient simulation: avoid O(N*T) if possible; consider event-based or batch updates.
  • Edge cases: people starting at or beyond L, watcher at L, direction changes at step 0 or T.
  • Time and space complexity analysis, and potential optimizations for large N and T.
  • Correctness: ensure the blocking condition is applied consistently each step.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.