At Planck Technologies, a Software Engineer plays a pivotal role in bridging the gap between cutting-edge research and robust, production-ready software systems. The engineering teams here work on highly complex, low-level systems, robotics integration, and advanced signal processing pipelines. Because our systems often operate at the intersection of hardware and software, your code will directly impact the performance, latency, and reliability of physical devices and experimental setups. This role is highly critical because Planck Technologies relies on software to interpret real-world physical data and control complex hardware modules. Whether you are optimizing a digital signal processing (DSP) algorithm, integrating the Robot Operating System (ROS) with custom Linux distributions, or writing high-performance C code, your contributions will drive our core technology forward. It is a challenging but deeply rewarding environment where academic rigor meets industrial-scale engineering. You will collaborate closely with hardware designers, research scientists, and systems engineers to turn complex mathematical models into highly optimized software. This requires not only exceptional coding skills but also a deep curiosity about how software interacts with physical hardware and networks.
Application Initiation
reportedCandidates begin the process through targeted applications or spontaneous outreach on internship and careers portals.
What to demonstrate
- Candidates begin the process through targeted applications or spontaneous outreach on internship and careers portals
- Depth in C programming
How to prepare
- Answer aloud and timed: Explain how you would optimize a C program to minimize memory footprint in an embedded environment.
- Answer aloud and timed: Describe the process of integrating and configuring ROS on a custom Linux distribution.
Technical Conversations
reportedEngage in deep technical discussions with senior systems engineers and researchers, focusing on engineering output and past projects.
What to demonstrate
- Engage in deep technical discussions with senior systems engineers and researchers
- Focusing on engineering output and past projects
How to prepare
- Answer aloud and timed: What are the primary differences between kernel space and user space in Linux, and why does it matter for real-time applications?
- Answer aloud and timed: How do you handle concurrency and race conditions when writing low-level multithreaded applications in C?
Technical Rounds
reportedParticipate in technical rounds that may emphasize software architecture or hardware integration, depending on the team.
What to demonstrate
- Participate in technical rounds that may emphasize software architecture or hardware integration, depending on the team
- Depth in C programming
How to prepare
- Answer aloud and timed: What programs or drivers have you written to interface directly with hardware peripherals?
- Answer aloud and timed: Walk us through a digital signal processing (DSP) pipeline you have designed or worked with in the past.
Final Offer Stage
reportedConclude the interview process with discussions leading to a potential job offer.
What to demonstrate
- Conclude the interview process with discussions leading to a potential job offer
- Depth in C programming
How to prepare
- Answer aloud and timed: How do you handle real-time signal processing constraints when system latency must be kept to a minimum?
- Answer aloud and timed: Explain the role of VLSI design principles when collaborating with hardware teams on software interfaces.
PracHub editorial advice for the preparation topics above.
Be ready to write code on the spot
During your technical rounds, you may be asked to write C or Python code to solve specific systems or algorithmic challenges. Keep your code clean, modular, and explain your thought process aloud as you write.
Emphasize your integration experience
Since our software interacts closely with hardware, highlight any experience you have with ROS, Linux configuration, or interfacing with microcontrollers and sensors.
Highlight your debugging skills
Writing code is only half the battle. Be prepared to talk about how you debug complex, asynchronous systems. Mentioning tools like GDB, Valgrind, or Wireshark can demonstrate your practical troubleshooting capabilities.
When explaining your past projects, structure your answers using the STAR method (Situation, Task, Action, Result)
Focus heavily on the "Action" phase, detailing the exact programming choices you made.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain how you would optimize a C program to minimize memory footprint in an embedded environment.
Explain how you would optimize a C program to minimize memory footprint in an embedded environment.
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
What are the primary differences between kernel space and user space in Linux, and why does it matter for real
What are the primary differences between kernel space and user space in Linux, and why does it matter for real-time applications?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
How do you handle concurrency and race conditions when writing low-level multithreaded applications in C?
How do you handle concurrency and race conditions when writing low-level multithreaded applications in C?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
What programs or drivers have you written to interface directly with hardware peripherals?
What programs or drivers have you written to interface directly with hardware peripherals?
Approach
- Say what the runtime actually does before reasoning about the code.
- Name what is shared across threads and what owns each piece of state.
- Identify the window where an invariant is briefly untrue.
- Distinguish a value from a reference to it, and say which one you handed out.
Follow-up
- What happens if two callers reach this at the same time?
- Where could this allocate more than you expect?
Implement a custom queue structure in C that is safe for single-producer, single-consumer scenarios.
Implement a custom queue structure in C that is safe for single-producer, single-consumer scenarios.
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
How would you optimize a search algorithm operating on highly constrained embedded hardware?
How would you optimize a search algorithm operating on highly constrained embedded hardware?
Approach
- Restate the input: its shape, its size, and what is guaranteed about it.
- Name the brute-force solution and its complexity before improving on it.
- Choose the data structure from the access pattern, not from familiarity.
- State the target complexity and say which constraint rules the naive version out.
Follow-up
- How does this change if the input no longer fits in memory?
- What is the worst case, and how likely is it on real data?
Replace offset paging on the resource feed with keyset
resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.
Approach
- Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
- Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
- Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
- Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.
Follow-up
- The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
- Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?
Stop tag and share joins from fanning out a page
resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.
Approach
- Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
- Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
- Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
- Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.
Follow-up
- The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
- A resource can be shared with the same user twice under different permissions. Does your count change, and should it?
Describe the process of integrating and configuring ROS on a custom Linux distribution.
Describe the process of integrating and configuring ROS on a custom Linux distribution.
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Walk us through a digital signal processing (DSP) pipeline you have designed or worked with in the past.
Walk us through a digital signal processing (DSP) pipeline you have designed or worked with in the past.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
Explain the role of VLSI design principles when collaborating with hardware teams on software interfaces.
Explain the role of VLSI design principles when collaborating with hardware teams on software interfaces.
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How do you design a robust network protocol for transmitting high-frequency sensor signals over a local networ
How do you design a robust network protocol for transmitting high-frequency sensor signals over a local network?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Given a stream of sensor data, how would you design an efficient data structure to keep track of the moving av
Given a stream of sensor data, how would you design an efficient data structure to keep track of the moving average?
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
Walk us through the architecture of your thesis project and explain the technical choices you made.
Walk us through the architecture of your thesis project and explain the technical choices you made.
Approach
- Fix the scope first: who calls this, how often, and what they do when it fails.
- Name the read and write paths separately; they rarely have the same bottleneck.
- Choose a partition key and say what query it makes expensive.
- State the consistency you need, and where you are willing to be stale.
Follow-up
- What breaks first when traffic grows ten times?
- How does this behave when that dependency is down for an hour?
What were the most significant engineering challenges you faced during your academic projects, and how did you
What were the most significant engineering challenges you faced during your academic projects, and how did you resolve them?
Approach
- Clarify what is being asked and what a complete answer contains.
- State your assumptions explicitly before working the problem.
- Say what you would check first and why it is the highest-information step.
- Work from the requirement backwards to the design.
Follow-up
- What assumption would you test first?
- How would you know your answer was wrong?
How did you integrate different software subsystems (e.g., combining Python scripts with compiled C binaries)
How did you integrate different software subsystems (e.g., combining Python scripts with compiled C binaries) in your past work?
Approach
- Say who the caller is and what they do when the call fails halfway.
- Define the identity of a request so a retry cannot double-apply it.
- Separate accepted, pending, failed and confirmed; they are different facts.
- Design the error taxonomy before the success shape; callers branch on it.
Follow-up
- What happens if the caller retries after a timeout?
- How does a client discover it is on an old version of this contract?
Exports duplicate a row range about once a week
Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.
Approach
- Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
- Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
- Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
- Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.
Follow-up
- The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
- You now count takeovers. What alert fires on that counter, and at what threshold?
Built from the rounds and topics Planck Technologies candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Planck Technologies loop
- Write out the reported sequence: Application Initiation, Technical Conversations, Technical Rounds, Final Offer Stage.
- For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.
Deliverable: A one-page map of the 4 reported rounds, with the weakest marked.
02Work C programming
- Spend the session on C programming, which Planck Technologies candidates report being tested on.
- Write one worked example in C programming and time yourself on it.
Deliverable: One timed worked example in C programming.
03Work ROS (Robot Operating System)
- Spend the session on ROS (Robot Operating System), which Planck Technologies candidates report being tested on.
- Write one worked example in ROS (Robot Operating System) and time yourself on it.
Deliverable: One timed worked example in ROS (Robot Operating System).
04Work Integrating ROS with Linux
- Spend the session on Integrating ROS with Linux, which Planck Technologies candidates report being tested on.
- Write one worked example in Integrating ROS with Linux and time yourself on it.
Deliverable: One timed worked example in Integrating ROS with Linux.
05Answer out loud: Systems & Low-Level Programming
- Answer aloud, timed: Explain how you would optimize a C program to minimize memory footprint in an embedded environment.
- Answer aloud, timed: Describe the process of integrating and configuring ROS on a custom Linux distribution.
Deliverable: Spoken answers to 2 reported Systems & Low-Level Programming question(s), under time.
06Answer out loud: Signal Processing & Hardware Interfacing
- Answer aloud, timed: Walk us through a digital signal processing (DSP) pipeline you have designed or worked with in the past.
- Answer aloud, timed: How do you handle real-time signal processing constraints when system latency must be kept to a minimum?
Deliverable: Spoken answers to 2 reported Signal Processing & Hardware Interfacing question(s), under time.
07Answer out loud: Data Structures & Algorithms
- Answer aloud, timed: Implement a custom queue structure in C that is safe for single-producer, single-consumer scenarios.
- Answer aloud, timed: How would you optimize a search algorithm operating on highly constrained embedded hardware?
Deliverable: Spoken answers to 2 reported Data Structures & Algorithms question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
How do you handle real-time signal processing constraints when system latency must be kept to a minimum?
How do you handle real-time signal processing constraints when system latency must be kept to a minimum?
Approach
- Pick a story where you made the decision, not one where you watched it.
- State the situation in two sentences and spend the rest on the reasoning.
- Give the blast radius: what could have broken, and what you measured.
- Name the disagreement and how you resolved it with evidence.
Follow-up
- What would you do differently if you ran that again?
- How did you know your change caused the improvement?
Tell callers you do not own that their integration breaks
A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.
Approach
- Establish the reader set empirically rather than from a wiki of owners: per-field usage counters keyed by principal, or access logs attributed to a consumer. State the blind spot of whichever you pick, since a consumer that reads the field only on a monthly job will not appear in a week of logs.
- Ship additive first. Populate the new field alongside the old one so no reader is forced to move, which is also what keeps a rolling deploy safe, because old and new instances answer the same requests at the same time and a rollback must still find the old shape present.
- Set the window from the slowest legitimate consumer's release cadence, not from your calendar, and decide separately what to do for a consumer with no release process at all, such as an external webhook endpoint you can only email.
- Convert silence into evidence before you rely on it: a short, low-traffic removal window that makes a still-dependent consumer fail visibly and loudly while you are watching, rather than at three in the morning after you have moved on.
Follow-up
- How would you detect a consumer that reads the field only during a monthly export?
- One caller refuses to move and has a commercial relationship behind it. What changes in your plan and what does not?
Argue against a design, lose, and commit anyway
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
Approach
- State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
- Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
- Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
- Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.
Follow-up
- What threshold on that alert would have proved you right, and did anyone ever look at it?
- If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?
- 01
How do you handle real-time signal processing constraints when system latency must be kept to a minimum?
- 02
A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.
- 03
Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.
How difficult is the technical interview at Planck Technologies?
The interview is of average to high difficulty. It focuses heavily on practical engineering foundations and your actual project experience rather than trick puzzle questions. If you have a solid grasp of C, Linux, and your own past projects, you will be well-prepared.
Planck Technologies Software Engineer candidate reports ↗I am applying to the Garching office but do not speak German. Will this be a problem?
Not at all. The working language and the entire interview process at our Garching b. München site are entirely in English. We welcome international talent and evaluate candidates purely on their technical merit and collaborative fit.
Planck Technologies Software Engineer candidate reports ↗How much should I prepare to discuss my thesis or academic projects?
You should prepare extensively. Interviewers will ask deep, probing questions about the software architecture of your projects, the specific programs you wrote, and how you integrated different technologies. Be ready to explain and defend your technical decisions.
Planck Technologies Software Engineer candidate reports ↗What is the typical timeline from application to offer?
The process typically takes between three to six weeks. This includes the initial review, technical screens, and the deep-dive technical rounds. We aim to keep candidates informed at every stage of the process.
Planck Technologies Software Engineer candidate reports ↗What topics does Planck Technologies test in interviews?
Planck Technologies interviews most often cover Algorithmic Thinking, Functional Requirements Gathering (Levantamento de requisitos), C programming, Scientific presentation (research talk), and Research Paper Implementation. The exact emphasis depends on the specific role you apply for.
Planck Technologies Software Engineer candidate reports ↗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.
- 01Planck Technologies Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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