Why Tractable?

We combine world-class AI research with real-world applications that make a difference. At Tractable, you’ll collaborate with brilliant minds, work on transformative projects, and contribute to technology that helps people when they need it most.

About the role

We’re building LUMA, a drive-through vehicle inspection scanner that combines multi-camera capture, active illumination, and multiple sensor modalities to generate high-fidelity vehicle imagery and measurements. We’re looking for an Embedded Systems Engineer to own and evolve the device-side software/firmware stack that controls cameras and sensors, synchronizes capture, and enables new measurement capabilities.

This role sits at the intersection of embedded software, hardware integration, and sensor/vision data processing.

What you’ll do

• Maintain and improve camera control software (triggering, timing, health monitoring, error recovery).

• Maintain and improve sensor control software (presence/distance/measurement sensors, calibration, fault handling).

• Develop new scanner capabilities.

• Implement signal processing pipelines (e.g., convert laser triangulation outputs into 2D tread-depth maps; post-process stereo depth results; filtering/denoising; coordinate transforms).

• Prototype quickly, then harden implementations to production-grade reliability.

• Support system integration and deployments: bring up new modules, validate in the lab/on-vehicle, debug issues, and ship fixes.

What we’re looking for

Core requirements

• Strong software engineering fundamentals (debugging, testing, reliability, version control).

• Experience integrating sensors/devices in real-world systems.

• Comfort working close to hardware: bring-up, wiring, and iterative troubleshooting.

• Ability to take ambiguous requirements and ship maintainable systems.

Relevant technical experience

• Embedded/edge platforms: Raspberry Pi, NVIDIA Jetson, Arduino (or similar).

• Protocols and interfaces: RS-485, CAN, Modbus, UART/I2C/SPI, GPIO.

• Linux-based device development: system services, supervision, logging, performance profiling.

• Container based application development: Docker or similar container runtimes.

• Sensor/vision data processing: filtering, calibration, synchronization, map generation.

Hands-on electronics

• Able to connect sensors to compute hardware safely and cleanly.

• Comfortable with basic soldering, crimping/connectors, and reading datasheets/wiring diagrams.
  

Preferred requirements

• Computer vision/depth sensing experience (stereo, structured light, LiDAR, triangulation).

• Multi-device synchronization (timestamps, trigger distribution, drift management).

• Queue based job management e.g. Redis worker queues.

• Production deployments (monitoring, remote updates, failure analysis).

• Python + C/C++ (and/or Rust/Go) in mixed systems.

• Familiarity with camera control APIs and image capture pipelines.

• Familiarity with IoT fleet management software such as AWS IoT, Balena Cloud, etc.

What success looks like

• Camera and sensor stacks run reliably for weeks with clear telemetry and graceful recovery.

• New capabilities move from prototype to validated pipeline to production-ready release.

• Hardware bring-up time decreases as tooling, test harnesses, and standards improv