Keysight Technologies · Software Engineer
Updated · 2026-09-24

Keysight Technologies Software Engineer
Interview Questions & Guide 2026

THE 60-SECOND BRIEF

As a Software Engineer at Keysight Technologies, you operate at the critical intersection of high-performance software development and cutting-edge hardware measurement technology. Keysight Technologies is a global leader in electronic design, simulation, and test solutions, supporting industries ranging from 5G telecommunications and aerospace to quantum computing and semiconductor manufacturing. In this role, your code directly controls high-precision test hardware, processes massive streams of high-frequency signal data, and delivers powerful graphical interfaces that allow engineers worldwide to design and validate next-generation technologies.

Seniority moves the scope further than the words in the title do. An earlier-career loop mostly checks that you implement something correctly and can reason about its cost, while a senior loop checks that you can pick between two defensible designs and say what you gave up.

Keysight Technologies candidates report 4 rounds · ≈ 3-5 weeks. The stages below are what candidates describe, not a published process.

Keep money in integer minor unitsScope every query and cache key by tenantBound blast radius with per-tenant concurrency limits

36 min read

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See the practice prompts

14Practice promptsAcross five skill areas
3With worked solutionsIncluded in the practice prompts

As a Software Engineer at Keysight Technologies, you operate at the critical intersection of high-performance software development and cutting-edge hardware measurement technology. Keysight Technologies is a global leader in electronic design, simulation, and test solutions, supporting industries ranging from 5G telecommunications and aerospace to quantum computing and semiconductor manufacturing. In this role, your code directly controls high-precision test hardware, processes massive streams of high-frequency signal data, and delivers powerful graphical interfaces that allow engineers worldwide to design and validate next-generation technologies.

The software engineering scope at Keysight Technologies spans full-stack instrument software, low-level driver development, cloud-connected analytics pipelines, and desktop applications using C++, C#,.NET, and Python. Depending on your team, you might build real-time digital signal processing (DSP) algorithms for oscilloscopes, develop test automation frameworks for wireless protocol validation, or write software libraries that enable quantum computing research. The impact of your work is immediate: missing a performance bottleneck or mathematical edge case in measurement software directly affects the accuracy of hardware validation across thousands of customer labs.

What makes this role compelling is the technical breadth required. You are not merely writing business logic; you are solving complex engineering problems where software design, memory efficiency, computer networking, and basic hardware fundamentals interact. Keysight Technologies values engineers who take ownership of the entire development lifecycle—from early concept and architecture to hardware integration, customer presentation, and long-term support.

01

Initial Screening

reported

Half of this call is the part candidates treat as small talk: start date, notice period, work authorisation and its timing, location and time zone, on-call, and the number. Those are what kill offers late, after several engineers have each spent a day. Surfacing a hard constraint now costs you nothing and occasionally buys you something, since a loop compressed to fit a competing deadline can usually only be arranged if it is asked for early. The common failure is deflecting the compensation question twice, then discovering at offer stage that the band never reached your number.

What to demonstrate

  • Whether your hard constraints are compatible with the role before a loop gets booked: earliest start, notice period, what authorisation you hold and when it needs action, days on site, willingness to carry a pager
  • Whether you give a compensation range with something behind it, such as current total compensation or a competing timeline, rather than leaving the band untested
  • Whether your stated timeline is real, since a competing deadline raised now is something scheduling can sometimes work around and the same deadline raised at offer stage usually is not

How to prepare

  • Write each constraint down in one line before the call and state them as facts rather than negotiating them live under a question you were not expecting
  • Set your range from two or three current data points for that level and location, and name the structure you are quoting in, so the number is comparable to the one they are holding
  • If another process is running, say where it stands and by when, and ask directly whether this loop can be scheduled inside that window
PracHub interview research ↗
02

Technical Interviews

reported

Most of the time lost in this format is not lost to thinking. It goes to a standard-library call you half-remember, an off-by-one in a loop bound, and a debugging loop that mutates code at random until something passes. When output is wrong, stop re-reading the whole function: take the smallest input that reproduces it and walk the state through by hand, printing intermediates if the environment allows. Guessing at a fix without a failing case you understand is how a five-minute bug becomes twenty, and the clock does not pause while you do it.

What to demonstrate

  • Whether you reach the right structure without a detour, and can write it from memory rather than only recall that one exists
  • Whether overflow is considered where the language has fixed-width integers, since a signed 32-bit value stops at 2,147,483,647 and then wraps in Java, is undefined behaviour in C++, and does not arise in Python, whose integers grow instead
  • Whether recursion depth is treated as a constraint on large inputs, given that CPython's default limit is 1000 frames and a deep recursion can exhaust the stack in any language where an iterative version would not
  • Whether a failing case is isolated and explained before any edit is made to the code

How to prepare

  • From an empty file and with no references open, implement the pieces you lean on most: a heap push and pop, an iterative DFS with an explicit stack, and a binary search whose midpoint is written lo + (hi - lo) / 2, which avoids the overflow that (lo + hi) / 2 can hit in a fixed-width integer type
  • Time yourself on the ten library calls you look up most, such as sorting with a custom comparator, splitting and joining strings, and finding the next key at or above a value in an ordered map, until the lookup is gone
  • Take a solution you know is broken and, before touching it, write one sentence naming the input, the expected value and the actual value. Repeat until you do it without deciding to.
PracHub interview research ↗
03

Behavioral Assessments

reported

Your first answer is not really what is scored. It buys the follow-up questions, and those decide the round. An interviewer with fifteen minutes takes one thread and pushes on it four or five times, so a story you can only tell at a single level of detail collapses under the third why. That is an argument for fewer stories known deeply rather than one prepared per prompt. Four or five pieces of work you can still explain down to the code you changed and the argument you had about it will cover nearly anything asked in this round.

What to demonstrate

  • Whether a story holds as the questioning moves from what you did to why that instead of the alternative, and then to what you would change knowing what you know now
  • Whether you can re-cut a project to answer the question actually asked rather than delivering a rehearsed block that answers an adjacent one
  • Whether your level of detail is chosen rather than habitual: going down to the schema when the question is about the data model, staying out of it when the question is about the person who disagreed with you

How to prepare

  • Pick four projects and write the chain out four levels deep for each: what you did, why that, why not the alternative, and what would have to be true for the alternative to have won. Where you cannot reach the fourth level, you have a placeholder rather than a story
  • Have someone ask why three times in a row on a single thread with nothing else added, and mark the point where you start repeating a sentence you already said. That point is where the interviewer stops learning anything
  • Build a one-page index instead of an answer bank: the common prompts in this round (disagreement, a failure that was yours, thin requirements, a deadline you missed, work you inherited) mapped to which of your four projects you would use for each, so the choosing is done now rather than while an interviewer waits
PracHub interview research ↗
04

Final Assessments

reported

Where the day includes a partner from product, design or data, that conversation is weighted like the technical ones and prepared for least. They are deciding one thing: whether having you in the room makes their decisions cheaper. That means options with costs attached, not implementation detail and not "it depends". An estimate someone can plan against — a range, the assumption that would push it to the high end, and what you would drop to hit the low one — is worth more than a confident single number, which everyone present already knows is wrong.

What to demonstrate

  • Whether an estimate comes as a range with the assumption most likely to break it, and states what a specific scope cut would actually buy
  • Whether a technical constraint is handed over as a choice with consequences on their side, rather than as a verdict they have no standing to argue with
  • Whether you establish what decision is on the table before proposing anything
  • Whether risk is raised while it can still change the plan, with the trigger that would confirm it, instead of reported afterwards as a slip

How to prepare

  • Take a project that shipped late and write the two-sentence warning you could have given three weeks earlier, naming what you would have needed decided at that point
  • Rehearse one estimate out loud until it arrives in three parts: the range, the single assumption that would blow it, and the smallest thing you would cut to protect the date
  • Rewrite an objection you have actually made — the "we can't do that" version — as two options with their costs, so the choice ends up with the person who owns it
PracHub interview research ↗

PracHub editorial advice for the preparation topics above.

01

Holding money in a floating-point type, or rounding it more than once

Binary floating point cannot represent 0.01 or 0.1 exactly, so sums drift and two code paths that should agree disagree by cents nobody can trace back. The fix is integer minor units or an exact decimal type end to end, with sub-cent rates expressed as scaled integers such as micro-units, because a per-request price genuinely is smaller than a cent. The second half of the trap is rounding position: rounding each line and then summing gives a different total from summing and rounding once, and half-up and half-even diverge systematically across many lines, so rounding must happen at one named place and every downstream reader must carry the rounded value rather than recompute it from quantity and rate.

02

Serialising a tenant's writes through select ... for update on a single counter row

It is the first change that makes a counter correct, and it caps that tenant's write throughput at roughly one divided by the lock hold time. A transaction that takes the lock, makes a network call and then commits holds it for the entire round trip: at 2 ms that is about 500 writes per second for the whole tenant, and the largest tenants are exactly the ones that exceed it. The damage then spreads, because every waiter holds a database connection while it queues, so one hot tenant drains the shared pool and the symptom presents as a site-wide latency incident rather than as a lock problem. The repairs are to shrink the critical section to a single statement, to shard the counter into per-(tenant, hour) or per-(tenant, bucket) rows and sum on read, or to batch in memory and flush periodically while accepting the bounded loss that batching implies.

03

Listing technologies instead of trade-offs

Name the property the design needs first, such as ordered range scans, multi-entity transactions, cheap appends, or a predictable p99, then pick something that provides it and say what it gives up in exchange. Almost any component is defensible once you state the requirement it satisfies and the one it sacrifices.

04

Answering a debugging question with a guess instead of a bisection

Give a procedure that halves the search space at each step: confirm the symptom reproduces, establish the last known-good version, input or timestamp, then bisect over commits, over the data, or over the layers of the request path. A plausible cause with no way to confirm it is the same move whether it happens to be right or wrong, which is why it scores nothing.

Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.

11 technical prompts3 include a worked solution

Given a dataset representing measurement time series, write pseudocode…

medium
data structures and algorithms

Given a dataset representing measurement time series, write pseudocode to detect anomalies or sudden signal spikes.

Approach
  1. Choose the data structure from the access pattern, not from familiarity.
  2. Restate the input: its shape, its size, and what is guaranteed about it.
  3. Name the brute-force solution and its complexity before improving on it.
Follow-up
  • How does this change if the input no longer fits in memory?
  • Which test case would catch an off-by-one here?

Explain how multithreading and parallel programming can be utilized to…

medium
data structures and algorithms

Explain how multithreading and parallel programming can be utilized to process large datasets without freezing a desktop GUI application.

Approach
  1. Choose the data structure from the access pattern, not from familiarity.
  2. Walk one small example through your approach before writing the whole thing.
  3. Name the brute-force solution and its complexity before improving on it.
Follow-up
  • What is the worst case, and how likely is it on real data?
  • Which test case would catch an off-by-one here?

Compare the pros and cons of using an array, a linked list, and a hash…

medium
data structures and algorithms

Compare the pros and cons of using an array, a linked list, and a hash map for storing dynamic instrument configuration parameters.

Approach
  1. Choose the data structure from the access pattern, not from familiarity.
  2. State the target complexity and say which constraint rules the naive version out.
  3. Restate the input: its shape, its size, and what is guaranteed about it.
Follow-up
  • Which test case would catch an off-by-one here?
  • How does this change if the input no longer fits in memory?

How do you detect cycles in a linked list, and what data structures wo…

medium
data structures and algorithms

How do you detect cycles in a linked list, and what data structures would you use to implement an efficient caching layer?

Approach
  1. Choose the data structure from the access pattern, not from familiarity.
  2. Walk one small example through your approach before writing the whole thing.
  3. State the target complexity and say which constraint rules the naive version out.
Follow-up
  • Which test case would catch an off-by-one here?
  • How does this change if the input no longer fits in memory?

Schedule ordered webhook retries with a heap of subscription queues

mediumWorked solution
heapschedulingbackoffhead-of-line-blocking

Design the in-memory scheduler for webhook delivery. Up to 20 million rows sit in status pending or failed_retryable across 200,000 subscriptions, each row carrying next_attempt_at and attempt_count, and each endpoint having a circuit breaker. Deliveries for one subscription must be attempted in order, so at most one attempt per subscription may be in flight. Support due(now), complete(delivery, outcome) and insert(delivery) in O(log S), where S is the subscription count rather than the delivery count. Give the backoff formula you schedule retries with.

Approach
  1. Key the global heap by subscription, not by delivery. Each subscription owns a FIFO of its due deliveries in event order; the heap holds one entry per eligible subscription, keyed by its head's next_attempt_at. That is 200,000 heap entries instead of 20 million, and it makes the one-in-flight rule structural rather than a check somebody can forget.
  2. due(now): peek the minimum. If its key is in the future, sleep until then instead of spinning. Otherwise pop it, move the subscription into an in-flight set, and do not re-push it. A subscription absent from the heap cannot be dispatched twice, which is precisely how ordering is preserved.
  3. complete: on success, drop the head and re-push the subscription keyed by its new head, or leave it out when the queue empties. On a retryable failure, increment attempt_count and set next_attempt_at = now + uniform(0, min(cap, base * 2^attempt)), sampled uniformly across the whole interval. That is full jitter; deterministic backoff re-synchronises the herd you just created.
  4. Circuit breaker: park the subscription in a second heap keyed by its half-open time, so an endpoint dead for six hours costs one heap entry and zero attempts rather than consuming worker slots. Admit exactly one probe at half-open and close the breaker only on its success.
  5. Say the price of the ordering guarantee out loud. One in-flight attempt per subscription means an endpoint answering in 10 seconds drains at 0.1 deliveries/second however many workers you run, and its backlog grows until it recovers. If the customer does not need order, allow k in flight and document delivery as unordered; that is the trade, and it is a product decision.
  6. All three operations are O(log S) with O(S) resident heap memory and the queues themselves backed by the store. The database-backed equivalent is a partial index on (subscription_id, next_attempt_at) where status in ('pending','failed_retryable') claimed with FOR UPDATE SKIP LOCKED, and the write-back must be fenced on lease_token so a worker that stalled and resumed cannot overwrite a newer attempt.
Worked solution 30 min
  1. Define the four structures explicitly: queues: subscription_id -> deque[delivery], ready: min-heap of (next_attempt_at, subscription_id), inflight: set[subscription_id], breaker: min-heap of (half_open_at, subscription_id).
  2. Write down the invariant you will assert after every operation: a subscription appears in at most one of ready, inflight and breaker, never in two.
  3. Implement due, complete and insert, then simulate 200,000 subscriptions with Zipf-distributed queue depths totalling 20 million deliveries.
  4. Add one endpoint that always times out after 10 seconds and one that always answers in 20 ms, then measure the fast endpoint's throughput with and without the per-endpoint breaker.
  5. Instrument heap size across the run.
EXPECTED RESULTHeap size stays at or below 200,000 regardless of the 20 million deliveries. The fast endpoint's throughput is unaffected by the dead one once the breaker trips. The dead endpoint's deliveries accumulate in their own deque and cost exactly one heap entry.
Follow-up
  • One subscription has 4 million queued deliveries. What stops it from starving the other 199,999, and what does your heap look like under that load?
  • A customer requests redelivery of last Tuesday's events. Where do those rows enter your structure, and what keeps them from reordering live traffic?
  • The process restarts. How much state do you rebuild, and what stops every subscription from being attempted in the same second?

Four days sample coding, design, fundamentals and the practical rounds at deliberately shallow depth, which is enough to surface the topics you did not know were in scope. That map, rather than a guess made on day one, decides where the last three days go.

Small steps. Visible outcomes.0 / 7 completed
ONE WEEK · YOUR PACE

Prepare, practise & reflect

One practical outcome each day. Spend longer where you need it.

0 / 7 done
01Coding, one pass at shallow depth
  • Solve one problem from each of six families, an array with two pointers, hash counting, binary search, a tree traversal, a graph traversal and one dynamic program, under a hard twenty-minute cap with no extensions, marking each finished, late, or stalled.
  • For every stall, write the exact move you could not make rather than the subject, so the note reads could not turn the recurrence into a loop rather than bad at dynamic programming.
  • Fix nothing today. The value of the pass is the unfixed record.

Deliverable: Six timed attempts marked finished, late or stalled, each stall carrying a named blocking move.

Practice prompt ↗Practice prompt ↗Worked solution ↗
02Design, one pass at shallow depth
  • Spend twenty minutes each on three different shapes, a read-heavy feed, a write-heavy ingest path, and something needing a transaction across two entities, stopping each at requirements, interface and data model.
  • After each, write the first question you could not answer, which is usually a number you could not estimate or a failure mode you had no vocabulary for.
  • Mark which of the three you would be most relieved not to be asked, and treat that as data rather than as a preference.

Deliverable: Three shallow designs, each with the first unanswerable question written at the bottom.

Practice prompt ↗Practice prompt ↗
03Fundamentals and the practical rounds
  • Answer eight short questions in writing at four minutes each, covering the material that fills the gaps between the big rounds: what happens between a URL and a rendered page, what an index costs on write, when a process is preferable to a thread, and what conditions a deadlock requires.
  • Do one thirty-minute practical task of the kind a take-home compresses: read an unfamiliar two-hundred-line file and write what it does, what you would change, and the one thing you remain unsure of.
  • Score every answer fluent, correct but slow, or absent, and keep the absent ones visible.

Deliverable: Eight scored short answers and one written reading of unfamiliar code.

Practice prompt ↗Practice prompt ↗
04The rounds that are about you, and the map
  • Deliver three behavioural answers aloud against a timer, a conflict, a failure you owned, and a decision made without enough information, marking any that ran past three minutes or contained no number.
  • Assemble the map: every marked item from days one to three on a single page, sorted by how likely it is to appear in your loop rather than by how uncomfortable it felt.
  • Choose exactly two areas for the remaining three days and write down what you are deliberately abandoning.

Deliverable: A one-page scored map of the whole surface area with two areas chosen and the rest explicitly abandoned.

Practice prompt ↗Practice prompt ↗Worked solution ↗
05First chosen area, to the depth you skipped
  • Work the higher-ranked area in four focused blocks, choosing items one level above where you stalled rather than repeating what already works.
  • After each block write the rule you extracted in one sentence with its precondition attached, since a rule carrying no precondition is exactly what fails under a variation.
  • Re-attempt the day-one or day-two item that exposed this area and compare against the original timing.

Deliverable: Four worked blocks, a timed re-attempt against the original, and three one-sentence rules with preconditions.

Practice prompt ↗Practice prompt ↗
06Second chosen area, where the gap is coverage rather than speed
  • Treat the second area differently from the first. Day five drilled something you could already half-do; this one is usually a topic you had simply never met, so build one worked reference example end to end and keep it, rather than attempting six problems badly.
  • Write down the vocabulary you were missing on day two or three, five terms at most, each with the one sentence that makes it usable in an answer rather than the textbook definition.
  • Redo the shallow attempt that exposed this area and note whether you now fail later in the problem, because moving the failure point is the realistic gain from a single day and is worth more than a score that did not change.

Deliverable: One worked reference example for the newly covered area, a five-term vocabulary list, and a note on where the failure point moved.

Practice prompt ↗Practice prompt ↗
07Reassemble the loop
  • Sit two rounds back to back with no gap, ordering them so the area you chose second comes last, because the map was built from rested, isolated attempts and the loop will reach your weaker area when you are already spent.
  • Write where the second round suffered from the first, which is normally the point at which structure collapses into narration.
  • Reduce the week to one page holding only the rules you can state without reading them.

Deliverable: Mock notes on cross-round carryover plus a one-page card of rules you can recite from memory.

Practice prompt ↗Practice prompt ↗Worked solution ↗

Expand any day for tasks and deliverables. Your progress is saved on this device.

Conflict answers where you were right and everyone came round are the weakest ones. Stronger: the evidence you went and collected, what would have changed your mind, and what you did in the weeks after the call went against you. Implementing a design you argued against, properly, is a specific and checkable behaviour.

Describe your experience using electronics test equipment like oscillo…

medium
behavioural and engineering judgement

Describe your experience using electronics test equipment like oscilloscopes or signal generators to verify software measurement outputs.

Approach
  1. Pick a story where you made the decision, not one where you watched it.
  2. Give the blast radius: what could have broken, and what you measured.
  3. Close with what you would do differently, concretely.
Follow-up
  • How did you know your change caused the improvement?
  • What did you decide not to do, and why?

Why are you interested in working at Keysight Technologies, and how do…

medium
behavioural and engineering judgement

Why are you interested in working at Keysight Technologies, and how does your background align with our electronic test and measurement focus?

Approach
  1. Close with what you would do differently, concretely.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Name the disagreement and how you resolved it with evidence.
Follow-up
  • What did you decide not to do, and why?
  • How did you know your change caused the improvement?

Estimate a tenant-leading index migration you have never run

hard
estimationonline migrationindex buildsuncertainty

Someone needs a date. usage_event carries an index on (occurred_at) and needs (tenant_id, occurred_at); the largest tenant holds roughly a hundred times the median tenant's rows, the table is partitioned daily with years of retention, and you have never run a migration on a table this large. Give an estimate you would defend: how you decompose the work, the two or three numbers you would go and measure first, the range and confidence you state, and what you commit to when the person asking needs a single date today.

Approach
  1. Refuse the bare number and then give one anyway, in the form that is actually useful: a range plus the measurement that collapses it. 'Four to eleven days; one afternoon building this index on a restored copy of the largest partition takes that to within a day' is an answer, while 'it depends' is not.
  2. Decompose by failure mode rather than into equal chunks, because that is where estimates go wrong. On a partitioned parent you create the index ON ONLY the parent, build each partition's index with CREATE INDEX CONCURRENTLY, then ALTER INDEX ... ATTACH PARTITION, at which point the parent index becomes valid. CONCURRENTLY does not block writes but scans each partition twice, waits out older transactions, cannot run inside a transaction block, and on failure leaves an invalid index you must drop concurrently and retry.
  3. Name the two unknowns that dominate and price them: build time on one restored partition of realistic size, and whether the planner actually chooses the new index for the skewed tenant, since selectivity for a tenant holding most of the rows is a different question from selectivity for the median tenant. Both are half-day measurements against a replica, and both are cheaper than being wrong by a week.
  4. State the assumptions the range is conditional on, because that is what makes a slip a re-estimate instead of a credibility event: no partition above a stated row count, one concurrent build at a time so it does not compete with ingest for I/O, and an ingest backlog that can absorb the added write amplification while both indexes exist.
  5. Budget the step nobody budgets: verification and the old index's removal. Dropping the old index is fast, but deciding it is safe to drop means confirming no plan still uses it, and that confirmation waits on real traffic across a full weekly cycle rather than on your patience.
  6. Answer the single-date request honestly. Commit to a date for the first checkpoint — the measured build number from the replica — and to re-estimating on that date, and say plainly what you are not committing to yet. A date with a scheduled re-estimate is worth more to the asker than a confident wrong one, and you should say why in those words.
Follow-up
  • The concurrent build fails half way through the largest partition. What is the state of the database and what do you do next?
  • Your estimate slips by sixty percent. Which assumption broke, and at what point would you have known?
  • The person asking needs the date for a customer commitment. Does your answer change?
  • 01

    Describe your experience using electronics test equipment like oscilloscopes or signal generators to verify software measurement outputs.

  • 02

    Why are you interested in working at Keysight Technologies, and how does your background align with our electronic test and measurement focus?

  • 03

    Someone needs a date. usage_event carries an index on (occurred_at) and needs (tenant_id, occurred_at); the largest tenant holds roughly a hundred times the median tenant's rows, the table is partitioned daily with years of retention, and you have never run a migration on a table this large. Give an estimate you would defend: how you decompose the work, the two or three numbers you would go and measure first, the range and confidence you state, and what you commit to when the person asking needs a single date today.

PracHub interview preparation framework ↗
Is this an official Keysight Technologies interview guide?

No. It is PracHub's own research and practice material for the Software Engineer role at Keysight Technologies. Rounds and questions reflect what candidates have reported, not a process Keysight Technologies has published, and they change over time. Confirm the current format and scope with your recruiter.

PracHub interview research ↗
How technical are the software engineer interviews at Keysight Technologies?

The interviews focus heavily on core computer science fundamentals, object-oriented concepts, and language mechanics rather than extreme competitive coding. While algorithmic efficiency matters, interviewers place equal weight on memory management, software design, and your ability to explain past engineering projects clearly.

PracHub interview research ↗
Do I need an Electrical Engineering (EE) background to get hired as a Software Engineer?

No, a formal Electrical Engineering degree is not strictly required. Candidates with pure Computer Science or Software Engineering degrees excel as long as they understand fundamental systems concepts, basic logic, and show willingness to learn how software interacts with physical test equipment.

PracHub interview research ↗
What programming languages are used most during the technical rounds?

Most technical interviews are conducted in C++, C#, or Python, depending on the target team. You are generally allowed to choose your preferred language during general coding sessions, but domain-specific rounds (such as low-level instrument software) will evaluate language-specific knowledge in C++ or C#.

PracHub interview research ↗
What is the purpose of the technical project presentation requested by some teams?

The presentation allows the interview panel to evaluate your engineering depth, communication clarity, and ability to structure technical narratives. It gives you an opportunity to lead the conversation by presenting a project you know thoroughly, explaining architectural decisions, trade-offs, and outcomes.

PracHub interview research ↗
Sources & methodology 3 sources ↗

No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.