Jump Trading Interview Questions & Experiences

Jump Trading·Software Engineer·Technical Phone Screen

Jun 2026

Jump Trading coding screen for a software engineer role. One problem, file permissions, seemed straightforward at first but the edge cases are where it gets you.

Given a batch of file queries where each entry contains an owner, a permission level, and a filename, identify which files are read-only. A file is read-only if none of the queries for it indicate write or any non-read permission.

“My first instinct was to just collect filenames and filter, but I kept second-guessing myself on what counts as non-read.”

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Jump Trading·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Jump Trading had me debug a workflow engine that handled nested sub-workflows. The whole session was basically chasing bugs through recursive execution logic, which sounds contained until you're 45 minutes in and still not sure where state is getting dropped.

Given a buggy workflow-management system that supports nested sub-workflows, identify and fix the issues in how the nested structures are traversed and executed.
How would you handle error propagation when a failure occurs deep inside a nested sub-workflow? Fix the existing implementation to correctly surface those errors to the parent.
Write tests covering deeply nested workflow cases and failure paths in the system you just debugged.
There's an ordering bug between parent and child steps in the workflow executor. Find and fix it.

“The recursion looked fine at first glance.”

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Jump Trading·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Jump Trading C++ developer loop, and the vector question ate up most of the session. Four parts, progressively harder, and the interviewer was clearly not satisfied with just knowing that you double the capacity.

Sketch the data layout for a simplified Vector<T> and implement size(), capacity(), operator[], and the fast path of push_back. What growth factor do you use when capacity runs out, and why does that make push_back amortized O(1)?
Why is 'new T[n]' the wrong way to allocate a vector's internal buffer? Show how you'd allocate raw storage, construct elements into it explicitly, and tear everything down correctly. Then implement the full rule of five.
If T's copy constructor can throw and it throws partway through relocating elements to a new buffer during push_back, what state is the vector left in? What exception-safety guarantee can you provide, and how do you implement the reallocation path to achieve it?
When relocating elements to a new buffer, how do you decide whether to move them or copy them? What standard utility handles this decision, and why does it matter for exception safety?
Which type traits let you optimize your vector implementation: specifically, which trait lets you use memcpy instead of element-by-element construction, which lets you skip destructor calls, and which governs the move-vs-copy decision during reallocation?
How would you extend this vector to support insert and erase in the middle, and what invalidation rules for iterators and references follow from your reallocation strategy?
How would you add an Allocator template parameter to this vector using std::allocator_traits? What specifically changes in the move-assignment operator?

“I went with the three-pointer layout (begin, end, end-of-capacity) which felt natural.”

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Jump Trading·Software Engineer·Technical Phone Screen

May 2026

Jump Trading SWE interview that went deep into C++ internals. Three questions, all technical, no fluff. The kind of interview where you realize pretty fast how much you've been taking the standard library for granted.

Walk me through the time complexity of vector::push_back, both amortized and worst-case, and explain how capacity growth works including reallocation, move vs. copy semantics, and what happens to iterators and references.
How is unordered_map implemented internally? Cover the hashing mechanism, bucket layout, collision handling, load factor and rehashing behavior, iterator/reference invalidation, and the time complexity guarantees for insert, find, and erase.
Explain the purpose of virtual functions in C++, how dynamic dispatch is implemented via vtables and vptrs, the runtime and memory overhead involved, when you need a virtual destructor, and how this compares to template-based static polymorphism.

“I knew the amortized O(1) answer but fumbled a bit when they pushed on the growth factor specifics.”

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Jump Trading·Software Engineer·Technical Phone Screen

May 2026

Jump Trading SWE interview with a stack-based string processing problem. Pretty algorithmic, felt like a coding screen more than anything else.

Given a string of whitespace-separated tokens (non-negative integers, '+', '-', 'DUP', 'POP'), simulate a stack machine: push integers, apply arithmetic ops on the top two elements, duplicate or pop the top, return an error on any illegal state, and return the top of the stack after all tokens are processed.

“The operand order for '+' and '-' tripped me up more than I expected.”

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Jump Trading·Software Engineer·Technical Phone Screen

May 2026

Jump Trading systems interview, probably for a software engineering role. One meaty question about file comparison that spiraled into a bunch of follow-ups on streaming and directories. Felt like a design question dressed up as a coding question.

Given a source file and a destination file, compare their contents and report whether they differ. If they do, describe what changed. How would you handle large files, line-based vs byte-based comparison, and extending this to a whole directory?

“Started with the obvious line-by-line diff approach and they immediately asked what happens when the file is 10GB.”

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Jump Trading·Software Engineer·Technical Phone Screen

May 2026

Jump Trading coding round, one question on array manipulation. Pretty standard stuff but the carry-propagation edge case is where people slip up if they're not careful.

Given an array of digits representing a non-negative integer (most significant digit first), increment the integer by one and return the resulting digit array.

“Straightforward on the surface.”

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Jump Trading·Software Engineer·Technical Phone Screen

Apr 2026

Jump Trading SWE interview with a math-flavored coding problem. Pretty focused session, just the one problem but they clearly wanted to see clean reduction logic and not just a brute force.

Given two arrays X and Y of the same length, where each pair X[i] and Y[i] represents a fraction, find the most frequently occurring fraction. Fractions that reduce to the same lowest terms count as the same. Return the count of the most common one.

“My first instinct was to just stringify the numerator and denominator and use that as a key, which would've broken on equivalent fractions like 2/3 and 4/6.”

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Jump Trading·Machine Learning Engineer·Technical Phone Screen

Apr 2026

Jump Trading MLE interview with two pretty dense algorithmic problems. Both had tight complexity requirements and the second one had a tricky correctness argument I wasn't fully prepared for. No behavioral stuff at all, just code and think-out-loud.

Given an array of daily stock prices and two patterns (buy and sell), where each pattern is a sequence of +1/-1 values representing day-over-day price direction, simulate a trading strategy: on each day, check if the tail of the price series matches the sell pattern (sell one share if you hold any) and/or the buy pattern (buy one share), processing sell before buy. Return the holdings array after each day. Aim for O(n) time and O(1) extra space.
Given a string and a set of disallowed 2-character substrings, repeatedly remove any occurrence of any disallowed pair until none remain. Return the final string length, and also discuss how you'd return the actual final string. Design an O(n) solution with minimal extra space and argue correctness.

“The pattern matching part seems straightforward until you realize zeros in the sign function break any match since the patterns only use -1 and 1.”

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Jump Trading·Machine Learning Engineer·Technical Phone Screen

Apr 2026

Interviewed for an ML Engineer role at Jump Trading. Two coding problems, both fairly algorithmic, nothing that screamed ML to me. The stock pattern one took most of my mental energy and I'm still not sure I nailed the edge cases.

You're given an array of daily stock prices along with two pattern arrays (sellPattern and buyPattern), each made up of 1s and -1s representing consecutive up/down price movements. A buy or sell action can only be triggered if the required pattern appears in the price history immediately before that day. Both can happen on the same day if both patterns match. Return an array where each element is the number of shares held after processing that day.
Given a string and a fixed set of substrings, repeatedly remove every occurrence of any substring in the set from the string until no more removals are possible. Return the final string.

“I spent way too long trying to figure out the exact pattern-matching logic before even touching the output array.”

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