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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating embedded vision systems, with strong capabilities in C/C++, embedded Linux, and computer vision deployment. Proven track record in technical leadership, system debugging, and optimizing performance across production hardware and software.
Highest-signal resume keywords
Embedded LinuxC/C++ ProgrammingComputer Vision DeploymentTechnical LeadershipSystem-Level Debugging
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Embedded SystemsConcurrencyIPCNetworkingStorageModel OptimizationCamera PipelinesImage ProcessingFault RecoveryRemote Diagnostics
Soft Skills
Clear CommunicationStrong OwnershipMentoring
Tools & Technologies
V4L2GStreamerTensorRTSNPEOpenVINOTFLite
Industry Keywords
Edge ComputingIoTRuggedized ProductsAutomotiveRobotics
Tech Stack
Tools & technologiesCloudIoTLinuxC++
About the role
Key responsibilities & impact- Own the production embedded vision stack, including camera capture, media pipelines, model inference, tracking, pre- and post-processing, device services, and cloud interfaces
- Design software for constrained resources, long uptimes, fault recovery, data integrity, and remote diagnostics
- Build observability for deployed devices, including metrics, logs, traces, crash data, health signals, and diagnostic tools
- Lead safe fleet releases with versioning, staged rollout, compatibility checks, rollback, and over-the-air update strategies
- Drive architecture and technical decisions across embedded Linux, hardware, vision, backend, and product boundaries
- Respond to production incidents, find root causes, and turn field learning into durable platform improvements
- Mentor engineers, lead design and architecture decisions, and establish standards for performance, reliability, testing, and maintainability
- Write and review code, debug systems in the field, and make architecture and trade-off decisions as a senior individual contributor
Requirements
What you’ll need- 7+ years building embedded or edge systems, with a track record of shipping and operating production hardware/software products
- Strong C/C++ skills
- Deep experience with embedded Linux, concurrency, IPC, networking, storage, and system-level debugging
- Hands-on experience deploying computer-vision or machine-learning inference on edge devices
- Experience with camera and image pipelines such as V4L2, GStreamer, codecs, synchronization, calibration, or equivalent systems
- Experience optimizing models with production runtimes or accelerators such as TensorRT, SNPE, OpenVINO, or TFLite
- Ability to balance accuracy, performance, reliability, security, development speed, and operational cost
- Demonstrated technical leadership across ambiguous, cross-functional work
- Clear communication and strong ownership
- Legally authorized to work in the United States
- Bonus: Experience with Qualcomm SNPE or other GPU/NPU-based edge platforms
- Bonus: Experience with multi-camera systems, sensor fusion, real-time perception, or video analytics
- Bonus: Experience with secure boot, device identity, signed updates, or hardening connected devices
- Bonus: Experience operating outdoor, automotive, robotics, IoT, or other ruggedized products at fleet scale
Benefits
Comp & perks- Competitive compensation
- Early-stage equity
- Meaningful ownership in a fast-moving startup environment
- Work with a small, experienced team where senior engineers have real technical influence
- Work that helps save lives and improve road safety