Engineering at TRACTIAN
The Engineering team at TRACTIAN is at the forefront of developing cutting-edge infrastructure, technologies, and products to harness the power of IoT data. Our team of talented Engineers collaborates to build robust systems, innovative solutions, and scalable platforms that drive Tractian's success. We are instrumental in shaping the company's decision-making process, optimizing operational efficiency, and delivering exceptional experiences to our consumers.
What you'll do
As an Instrumentation & Test Engineer, you will be responsible for designing, implementing, and validating physical measurement systems in our industrial testing laboratory.
Your mission is to ensure that sensor data collected from machines is physically valid, accurate, and statistically reliable for advanced analysis and AI model development. This includes instrumentation on equipment such as motors, gearmotors, compressors, fans, centrifugal pumps, and custom test benches.
You will lead the Design of Experiments (DoE), defining how to measure—not just collecting data. You will work closely with mechanical, automation, and data science teams to define acquisition strategies, select appropriate sensors, and configure data acquisition systems using platforms such as HBK (HBM), Dewesoft, Siemens, and NI (National Instruments).
Your work directly impacts the quality of the physics-based datasets used to train our AI models. While your core focus is instrumentation, signal analysis, and electrical integration, you’ll also assist in mechanical setups to ensure test environments are consistent and acquisition-ready.
Note: This is a hardware-focused role involving physical instrumentation in a laboratory environment. Ideally suited for Electrical/Mechatronics Engineers or Physicists, not traditional IT/Data Engineering profiles.
Responsibilities:
Experimental Design & Analysis: Lead the Design of Experiments (DoE), defining acquisition parameters, sensor requirements, sampling frequencies, and test methodologies to guarantee repeatability and statistical reliability.
Signal Validation: Perform immediate signal analysis (time & frequency domain) to verify data quality before it enters the AI pipeline, ensuring physical phenomena are correctly captured.
Instrumentation Setup: Select, install, and validate industrial and scientific sensors (vibration, temperature, pressure, torque, strain, flow), ensuring proper mounting, calibration, grounding, shielding, and overall signal integrity.
DAQ Operation: Configure and operate high-fidelity DAQ systems (e.g., HBK/HBM, Dewesoft, Siemens, NI), managing channel setups, filtering, synchronization, and triggering for complex test campaigns.
Automation Scripting: Develop and maintain Python-based tools specifically for hardware automation and signal processing (using libraries like Scipy/Numpy) to streamline data ingestion and validation.
System Integration: Work closely with mechanical and automation teams to ensure test benches are properly instrumented, electrically integrated, and safe for operation.
Documentation: Ensure traceability and comprehensive documentation of test configurations, wiring diagrams, sensor setups, DAQ settings, and calibration routines.
Troubleshooting: Diagnose and resolve issues related to electrical noise, grounding loops, synchronization failures, connector faults, or hardware limitations.
Continuous Improvement: Optimize acquisition workflows, tooling, and laboratory best practices to increase testing throughput and data reliability.
Requirements:
Degree in Electrical Engineering, Electronics Engineering, Mechatronics, Physics, Computer Engineering, or a related field. (Candidates with equivalent experience in data acquisition or experimental testing environments are also encouraged to apply.)
Advanced English and Portuguese.
Availability to work on-site in São Paulo (Chácara Santo Antonio - Zona Sul).
Hands-on experience with data acquisition systems and laboratory instrumentation in industrial, automotive, aerospace, or experimental R&D environments.
Familiarity with DAQ hardware and software platforms, such as HBK/HBM, Dewesoft, Siemens, or NI (National Instruments).
Strong understanding of sensor physics, signal conditioning, sampling theory, noise mitigation, grounding, and measurement uncertainty.
Proficiency in Python, with a focus on Signal Processing and acquisition automation (not just general data manipulation).
Experience working with time-series data and synchronous multisensor setups.
Ability to operate in experimental or laboratory environments, comfortable with physical tasks (cabling, mounting sensors).
Strong problem-solving skills related to instrumentation and signal integrity.
Bonus Points:
Experience working in automotive, aerospace, or NVH laboratories, where high-precision data acquisition is standard.
Strong background in vibration analysis, signal processing, or frequency-domain techniques (FFT, spectral analysis, filtering).
Familiarity with strain gauge measurements, Wheatstone bridges, and instrumentation amplifiers.
Experience with MATLAB or LabVIEW for signal processing or measurement workflows.
Knowledge of synchronization techniques (PTP, GPS timing, hardware triggering).
Exposure to machine learning workflows, understanding how physical data feeds into feature extraction.
Hands-on experience designing or building custom test fixtures or sensor mounts.
Experience managing large experimental datasets and knowledge of SQL or Time-Series databases for long-term data storage and traceability.
