Jobs at Humble Robotics

Build and optimize real-time on-vehicle software for autonomous trucks, including data logging, cross-compilation pipelines, performance instrumentation, testing/CI, and integrations with ML, firmware, cloud, and fleet systems.

Drive end-to-end planning and delivery of cross-functional engineering programs for an autonomous vehicle platform. Define scope, schedules, dependencies, and success criteria; coordinate hardware, software, robotics, and manufacturing teams; manage risks, design reviews, validation/testing, documentation, and stakeholder communications; improve program processes and tooling.

Lead integration and system-level design for autonomous electric vehicle subsystems across mechanical, electrical, and software domains. Define architectures and interfaces, perform performance, safety, and reliability analysis, plan and execute vehicle-level testing and validation, troubleshoot system-level issues, manage requirements, and support deployment and field resolution.

Own and improve sensor extrinsic calibration and localization systems for autonomous trucks. Develop evaluation metrics and fleet-scale frameworks, debug real-world failures, and collaborate across autonomy, vehicle software, and data teams to tighten sensor geometry and state-estimation pipelines.

Design and maintain pipelines and tooling to ingest, validate, model, and serve multi-modal driving data for ML training, evaluation, and debugging. Collaborate with ML, vehicle software, curation, and fleet teams to scale the data stack and make datasets discoverable and queryable.

Optimize and deploy neural network models for onboard inference on embedded GPUs using TensorRT and custom CUDA kernels. Profile and reduce end-to-end latency across the autonomous stack, build and maintain C++/Rust real-time software infrastructure, implement quantization/pruning, and collaborate with ML and vehicle systems engineers to meet real-time safety and performance constraints.

Develop and maintain safety-critical, real-time embedded firmware for automotive ECUs. Work across board bring-up to production: bootloaders, drivers, RTOS configuration, automotive communications, hardware-software debugging, testing (unit, integration, HIL), manufacturing test support, and field issue root-cause analysis.

Design and bring up electronic hardware for autonomous vehicles end-to-end: schematic/layout with Altium, PCB bring-up and debugging, integrate sensors/compute/actuators, run lab tests with scopes and logic analyzers, collaborate with Mechanical, Firmware, and Systems engineers, and document test results and issues.

Build and maintain Python-based simulation pipelines and tooling for closed-loop testing, synthetic data generation, and sensor simulation. Integrate neural rendering methods (Gaussian splatting, NeRFs, world models) into the sensor stack, expand scenario libraries and benchmarks, and collaborate with ML/autonomy teams to reduce sim-to-real gaps and support model training.

Design, implement, tune, and validate real-time trajectory generation and control systems for autonomous trucks. Develop vehicle dynamics models, state estimation and sensor fusion, perform SIL/HIL testing and on-vehicle experiments, debug using logs/telemetry, integrate ML path outputs, and maintain controls codebase in Rust with safety and real-time performance focus.

Lead end-to-end design and delivery of the electric powertrain system (battery, HV distribution, motors, inverters, drivetrain). Define system architecture, perform system-level modeling and validation, integrate battery/BMS and thermal strategies, oversee prototype builds and testing, manage suppliers, and ensure HV safety, durability, and production readiness.

Own system-level requirements and architecture for an autonomous vehicle platform. Decompose vehicle requirements into subsystem/component requirements, run design reviews, drive verification/validation, partner with Mechanical, SW/Autonomy, and Functional Safety teams, and lead root-cause analysis and requirement-based improvements.

Lead the end-to-end functional/system safety lifecycle for an autonomous vehicle program: hazard analyses, safety requirements, safety case/evidence, and verification strategy across simulation and vehicle testing. Drive safety-critical architecture decisions, ensure traceability from requirements to tests, establish lightweight safety processes, and guide teams on relevant standards (ISO 26262, SOTIF, UL 4600). Collaborate across autonomy, vehicle platform, embedded/compute, simulation, and test to produce safety evidence for internal and external review.

Design, prototype, and validate mechanical systems for large autonomous vehicles. Create CAD models and drawings, build and test hardware in-shop, integrate sensors and subsystems, manage sourcing and vendors, perform root cause analysis, and support field testing and deployments.

Design, build, and scale ML infrastructure: ingest vehicle sensor data, create batch pipelines for dataset curation, run distributed GPU training, and ensure performance, observability, efficiency, and security across the ML pipeline while partnering with ML teams.