Interview scorecard template

Quantum Computing Engineer interview scorecard

Evaluate Quantum Computing Engineer candidates across 4 weighted areas: theoretical command, from theory to hardware or code, research judgement, and explaining it to non-specialists. Theoretical command leads at 35%, so probe command of qubit physics: transmon Hamiltonians, decoherence channels (T1, T2 echo), gate calibration theory, and error correction codes such as surface. Use the rubric to compare role-specific evidence consistently.

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frontier research deep techcryogenicsqiskitquantum error correctionsuperconducting qubits
TL;DR
For theoretical command, look for evidence the candidate derives gate fidelity limits from noise models, cites measured T1/T2 numbers, and explains threshold assumptions behind surface code overhead. For from theory to hardware or code, look for evidence the candidate names devices they calibrated or code they merged, with before and after fidelity, coherence, or compilation depth figures. Apply the written 1–5 anchors to every answer, record the evidence behind each rating, and use the factor weights to reach a consistent overall assessment.
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Theoretical command

35% weight

Probe command of qubit physics: transmon Hamiltonians, decoherence channels (T1, T2 echo), gate calibration theory, and error correction codes such as surface or bosonic codes.

Evidence to listen for

  • Explains the underlying theory at the level the role demands, and can go a layer deeper when pushed
  • Knows which results are established and which are contested
  • Distinguishes their own contribution from the field's
  • Comfortable saying where the theory runs out

Five-point scoring guide

1
Poor

Recites terminology without understanding; cannot go one layer deeper.

2
Needs Improvement

Surface familiarity; conflates established results with speculation.

3
Satisfactory

Solid grasp of the core theory; thin at the frontier.

4
Very Good

Strong command; separates settled results from open questions.

5
Excellent

Derives gate fidelity limits from noise models, cites measured T1/T2 numbers, and explains threshold assumptions behind surface code overhead.

02
Evaluation factor

From theory to hardware or code

30% weight

Ask what they physically built or coded: pulse schedules in Qiskit Pulse or QuA, dilution fridge wiring, FPGA control stacks, or transpiler passes shipped to users.

Evidence to listen for

  • Has built, simulated, or run something real, not only published about it
  • Knows the gap between the idealised model and the actual apparatus or system
  • Names the practical constraint that dominates in real conditions
  • Can describe a result that did not match prediction

Five-point scoring guide

1
Poor

Purely theoretical; no contact with implementation.

2
Needs Improvement

Some exposure but unaware of practical constraints.

3
Satisfactory

Has implemented work; understands the main real-world limits.

4
Very Good

Strong practical record; articulate about theory-versus-reality gaps.

5
Excellent

Names devices they calibrated or code they merged, with before and after fidelity, coherence, or compilation depth figures.

03
Evaluation factor

Research judgement

20% weight

Test how they choose experiments: deciding between randomized benchmarking and gate set tomography, killing a qubit design, or judging when a fidelity gain is real versus drift.

Evidence to listen for

  • Chooses problems by tractability and value, not novelty alone
  • Knows when to abandon a line of work
  • Reads and evaluates others' results critically
  • Can say what would falsify their own approach

Five-point scoring guide

1
Poor

Chases novelty; no sense of tractability or when to stop.

2
Needs Improvement

Weak problem selection; persists past the point of value.

3
Satisfactory

Reasonable judgement within a defined programme.

4
Very Good

Selects problems well and knows when to abandon a line.

5
Excellent

Describes abandoning a promising approach on evidence, and distinguishes statistical fluctuation from genuine improvement using repeated characterization runs.

04
Evaluation factor

Explaining it to non-specialists

15% weight

Judge how they brief non-physicists: explaining error mitigation limits to product teams, setting realistic expectations with customers, or writing up results for funders and program managers.

Evidence to listen for

  • Explains the work to an engineer, an executive, or a funder without either mystifying or dumbing it down
  • Writes clearly
  • Collaborates across disciplines
  • Makes the case for resources in terms the audience cares about

Five-point scoring guide

1
Poor

Cannot communicate outside their specialism.

2
Needs Improvement

Explanation is either impenetrable or hollow.

3
Satisfactory

Adequate with technical peers; less effective with lay audiences.

4
Very Good

Explains clearly to specialists and non-specialists alike.

5
Excellent

Explains why a workload is not yet quantum-advantaged in plain terms, without overselling, and adjusts depth for executives versus hardware peers.

Evidence-led prompts

Interview questions for a Quantum Computing Engineer

Use these prompts to surface evidence for the weighted factors above and compare candidates against the same role-specific criteria.

  1. 01

    What is your experience with quantum hardware?

  2. 02

    Can you discuss a specific project where you applied quantum computing to a problem?

  3. 03

    Have you worked with quantum computing frameworks?

  4. 04

    Can you describe your experience with quantum algorithms and their implementation?

  5. 05

    What is your experience with quantum gates and building circuits?

See the complete Quantum Computing Engineer question set
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