Sensor / Instrumentation Engineer

About the Role

We’re building instruments that treat the air in a room (and across facilities like data halls) as a measurable field. That only works if sensors are placed intelligently, calibrated rigorously, and tied to a metrology story that survives real deployments: airflow, stratification, thermal gradients, condensation risk, duct effects, and “the room is lying to you” edge cases.

This role owns the bridge between physical reality and the data products: where sensors go, what they mean, how they drift, and how we prove it.

What You’ll Do

• Sensor placement & field mapping design: define placement strategies to resolve gradients (not just averages), including rack-level and hot/cold aisle contexts.
• Instrumentation plans for deployments: create practical install plans (mounting, shielding, cable routing, cadence, service access) that keep measurements stable and repeatable.
• Calibration routines & intervals: design factory + field calibration procedures, intervals, acceptance criteria; handle drift, hysteresis, and aging.
• Metrology & traceability: establish reference standards, uncertainty budgets, and traceable methods; define what “accuracy” means for gradient sensing vs point sensing.
• Environmental edge cases: account for condensation, wet-bulb effects, turbulence, thermal lag, sensor self-heating, enclosure and placement-induced bias.
• Validation experiments: run controlled studies (step changes, spatial scans, fan-speed sweeps) to verify inferred gradients match reality.
• Data quality flags: define QC signals and rules (stuck sensors, response-time anomalies, cross-sensor consistency checks, out-of-range behavior).
• Collaboration with systems/algorithms: provide constraints and calibration truth needed for co-timing, cancellation, and window validity gating.

Concrete Deliverables

• A sensor placement playbook (by environment type): cigar room, small mechanical room, data hall, containment edges, return-air paths—what to place where and why.
• A calibration protocol suite: field kit procedures, required references, step-by-step scripts, pass/fail thresholds, and calibration receipts.
• An uncertainty budget for key measurements (RH, temperature, dew point, airflow proxies) and how uncertainty propagates into gradient inference.
• A validation report framework: test plans + expected signatures + red flags that prove installations work.
• A QC/health rule set that the pipeline can enforce automatically.

Required Qualifications

• Hands-on experience with environmental sensing (humidity/temperature and ideally airflow), instrumentation, and field deployments.
• Strong understanding of calibration and metrology: uncertainty, drift, traceability, reference standards, and documentation.
• Ability to design experiments that separate sensor artifacts from real environmental variation.
• Comfort working with data (basic analysis, QC metrics) and communicating physical interpretations to software teams.

Preferred Qualifications

• Experience in data centers, HVAC instrumentation, building management systems (BMS), or industrial monitoring environments.
• Familiarity with psychrometrics (dew point, wet bulb, enthalpy) and how airflow patterns shape gradients.
• Experience with sensor technologies: capacitive RH, RTDs/thermistors, ultrasonic or thermal anemometry (or practical airflow proxies).
• Experience designing robust field hardware: enclosures, filters, fixtures, contamination mitigation.

How You’ll Be Measured (First 60–90 Days)

• You produce a clear placement + calibration standard that operators can follow without improvising.
• You run at least one validation study showing gradient-sensing behavior is real, repeatable, and bounded by a quantified uncertainty story.
• You define QC rules that reduce bad deployments and catch drift early.
• You reduce ambiguity: fewer “is this real?” debates because the metrology is explicit.

Working Style

• You don’t accept “RH = 52%” without asking: where, how mounted, how calibrated, and what the airflow was doing.
• You like procedures that are rigorous but not fragile—field-tech proof.
• You think in error bars, not just readings.

Title & Level

Sensor / Instrumentation Engineer (mid-to-senior; can scale to Staff with ownership of standards and validation), partnering with systems, firmware, and algorithm teams.