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Privacy-Enhancing Computation Engineer interview scorecard

Pre-screening scorecard for Privacy-Enhancing Computation Engineer candidates.

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frontier research deep techdifferential privacyhomomorphic encryptionsecure multiparty computationtrusted execution environments
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 MPC protocols (garbled circuits, secret sharing), lattice-based FHE schemes such as CKKS or BFV, and formal differential privacy budgets including composition and sensitivity analysis.

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

States concrete security models (semi-honest versus malicious), derives epsilon-delta budgets unprompted, and names the assumptions each protocol actually relies on.

02
Evaluation factor

From theory to hardware or code

30% weight

Ask which libraries they wrote or extended: OpenFHE, SEAL, MP-SPDZ, tf-encrypted, OpenDP, or SGX/SEV enclaves, plus measured latency and ciphertext expansion figures.

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

Points to merged code or deployed pipelines with real benchmarks: bootstrapping cost, packing strategy, wall-clock time on production-sized datasets.

03
Evaluation factor

Research judgement

20% weight

Test how they choose between DP noise, secure aggregation, and enclaves for a given threat model, and when they judged a privacy technique not worth the compute cost.

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

Frames choices against adversary capability and utility loss, and cites a case where they rejected a fashionable primitive for sound reasons.

04
Evaluation factor

Explaining it to non-specialists

15% weight

Assess how they explain privacy loss to legal, product, and regulators mapping guarantees to GDPR, HIPAA de-identification, or internal privacy review sign-off.

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

Translates epsilon values and side-channel risk into plain business language without overclaiming anonymity, and has convinced non-technical reviewers to approve.

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