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
Technical depth
35% weight
Check depth in sensor fusion and on-device inference: mmWave radar versus PIR presence detection, TinyML quantisation on ESP32 or Nordic silicon, BLE mesh, Zigbee, Thread and Matter stacks.
Evidence to listen for
Explains the physics or mechanism behind their work, not just the tooling
Names the standards, tolerances, and constraints they designed against
Can defend a design decision under follow-up questions
Distinguishes what they personally engineered from what the team delivered
Five-point scoring guide
1
Poor
Cannot explain the fundamentals of their own stated specialism.
2
Needs Improvement
Knows the vocabulary but not the underlying mechanism; struggles under follow-ups.
3
Satisfactory
Solid working knowledge for the role; depth thins out on edge cases.
4
Very Good
Strong command of the domain; explains trade-offs and defends decisions well.
5
Excellent
Explains radar occupancy false-positive tradeoffs, names quantisation and latency budgets, and distinguishes Thread from Zigbee routing behaviour precisely.
02
Evaluation factor
Work that shipped
30% weight
Ask for deployed ambient systems: room count, sensor node totals, uptime achieved, battery life per node, and whether occupancy or activity recognition models ran in production or a demo lab.
Evidence to listen for
Names specific programmes, parts, or systems that reached production or field use
States their own scope inside the project
Can give measured outcomes: yield, cycle time, cost, failure rate
Explains what went wrong and what they changed
Five-point scoring guide
1
Poor
No delivered work; experience is coursework, lab-only, or purely observational.
2
Needs Improvement
Contributed to projects but cannot say what shipped or what their part was.
3
Satisfactory
Has delivered real work; outcomes described without numbers.
4
Very Good
Names shipped work and their scope, with some measured results.
5
Excellent
Cites a live deployment with node counts, measured battery life, model accuracy in the field, and post-launch ownership.
03
Evaluation factor
Diagnosis under uncertainty
20% weight
Probe how they chased intermittent faults: RF interference in dense 2.4GHz environments, sensor drift, phantom presence events, gateway dropouts, and what logging or replay tooling isolated the cause.
Evidence to listen for
Describes a real failure they chased to root cause
Shows a method: isolate variables, reproduce, measure, eliminate
Distinguishes correlation from cause
Says what they ruled out and why, not only what the answer turned out to be
Five-point scoring guide
1
Poor
No diagnostic method; guesses or escalates immediately.
2
Needs Improvement
Trial and error with no structure; cannot explain how they narrowed the cause.
3
Satisfactory
Reasonable method on familiar problems; less structured on novel ones.
4
Very Good
Clear systematic approach with a real root-cause story.
5
Excellent
Describes narrowing a flaky presence bug using packet captures or replayed sensor traces, not guesswork or blanket firmware rewrites.
04
Evaluation factor
Working across the org
15% weight
Assess collaboration with UX, facilities, security and privacy reviewers: consent handling, GDPR or data minimisation choices, and how they negotiated sensing scope with building owners or product managers.
Evidence to listen for
Explains technical constraints to non-technical stakeholders without condescension
Has negotiated scope, cost, or timeline with manufacturing, product, or suppliers
Documents decisions so others can act on them
Takes review feedback without defensiveness
Five-point scoring guide
1
Poor
Cannot communicate outside their specialism; dismissive of other functions.
2
Needs Improvement
Communication gaps cause rework; avoids stakeholder contact.
3
Satisfactory
Works adequately with other teams; documentation is thin.
4
Very Good
Communicates clearly across functions; reliable collaborator.
5
Excellent
Recounts reshaping a sensing design after privacy or facilities pushback, naming the stakeholders and the compromise reached.
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