Openai·Machine Learning Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

May 2026Remote

Summary

OpenAI ML Engineer interview with a meaty systems coding question. The whole thing was basically one big design-and-implement problem, which I wasn't fully expecting for this role.

Questions Asked (1)

Build a tick-based simulation of a coffee-shop queue. The shop has multiple baristas each with their own service time, customers arrive with an arrival time and order complexity, and the system uses a single FIFO queue. Implement a Simulation class with a run() method that returns total customers served, average wait time, and max queue length. The design should allow new event types to be added without rewriting the core loop. Also discuss data structure choices and how you'd extend it to multiple locations or menu tiers.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

I spent the first few minutes just staring at the tick loop logic trying to figure out if I needed a heap or a plain counter for barista availability.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining the core entities (Customer, Barista, Event, Simulation). Then outline an event-driven architecture with a priority queue for events and a FIFO queue for customers, ensuring extensibility via an event handler registry. Finally, discuss data structure trade-offs and scaling to multiple locations or menu tiers.

Pro tip: Emphasize that the event loop should be agnostic to event types by using a handler mapping, and mention that metrics like average wait time should be computed incrementally to avoid storing all wait times.

1. Clarify Requirements and Define Entities

Ask clarifying questions about arrival distribution, service time variability, and metrics definitions. Define classes for Customer, Barista, Event, and Simulation with clear responsibilities.

2. Design Event-Driven Core Loop

Use a priority queue (min-heap) for events ordered by time. The loop pops the next event, dispatches to a handler based on event type, and schedules new events. Handlers are registered in a dictionary to allow easy addition of new event types.

3. Implement Queue and Barista Management

Use a FIFO queue (collections.deque) for customers. When a barista becomes free, dequeue the next customer and schedule a service completion event. Track queue length and wait times for metrics.

4. Compute and Return Metrics

Maintain running totals for customers served, total wait time, and max queue length. At the end of simulation, compute average wait time as total wait time divided by customers served.

5. Discuss Extensibility and Scaling

Explain how to add new event types (e.g., order cancellation) by adding a handler. For multiple locations, replicate the simulation per location or use a multi-queue system. For menu tiers, add attributes to Customer and adjust service time based on complexity.

Key Points to Mention

Use of priority queue (heap) for event scheduling to ensure O(log n) insertion and extraction.
FIFO queue implemented with deque for O(1) enqueue and dequeue.
Event handler registry (dictionary mapping event type to handler function) for extensibility.
Incremental computation of metrics to avoid storing all wait times.
Trade-offs: priority queue vs. sorted list; deque vs. list for queue.
Scaling to multiple locations: either independent simulations or a central event queue with location tags; menu tiers: add complexity attribute and adjust service time.

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