Interview scorecard template

Advanced Robotics Engineer interview scorecard

Evaluate Advanced Robotics Engineer candidates across 4 weighted areas: technical depth, work that shipped, diagnosis under uncertainty, and working across the org. Technical depth leads at 35%, so probe the specific layer they own: kinematics, control, perception, or manipulation, and the theory behind it. Use the rubric to compare role-specific evidence consistently.

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engineering applied scienceautomationcontrolsmechatronicsrobotics
TL;DR
For technical depth, look for evidence the candidate deep command of their layer, from control theory through to the hardware it runs on. For work that shipped, look for evidence the candidate names robots that ran in production or the field, with uptime, throughput, or accuracy figures they owned. 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

Technical depth

35% weight

Probe the specific layer they own: kinematics, control, perception, or manipulation, and the theory behind it.

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

Deep command of their layer, from control theory through to the hardware it runs on.

02
Evaluation factor

Work that shipped

30% weight

Look for robots that ran outside a demo: deployed cells, fielded units, or systems in continuous operation.

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

Names robots that ran in production or the field, with uptime, throughput, or accuracy figures they owned.

03
Evaluation factor

Diagnosis under uncertainty

20% weight

Test how they debug a system where mechanical, electrical, and software causes all look identical from the outside.

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

Isolates across mechanical, electrical, and software layers methodically, with a real root-cause story.

04
Evaluation factor

Working across the org

15% weight

Check how they work with operations and safety when an autonomous system shares space with people.

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

Works closely with operations and safety on human-robot interaction, and documents the reasoning.

Evidence-led prompts

Interview questions for a Advanced Robotics Engineer

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

  1. 01

    Which layer of the stack do you personally own, and how deep does your experience with ROS or ROS2 go?

  2. 02

    Walk me through your experience with control systems on a robot: what did you tune, and how did you know it was right?

  3. 03

    How do you approach designing algorithms for robotic perception, and where do your pipelines usually break?

  4. 04

    What sensors have you integrated onto a robot, and what surprised you about one of them in the field?

  5. 05

    Describe a project where you worked with autonomous navigation systems. How many units ran, and for how long?

See the complete Advanced Robotics Engineer question set
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