About Us

SkyServe is pioneering edge-native satellite architectures and orbital artificial intelligence. Through our flagship software stack—STORM (space-grade edge OS and flight container runtime) and SURGE (on-orbit AI acceleration and smart-downlink engine)—we run autonomous algorithms directly on satellite payload compute modules in Low Earth Orbit (LEO).

Position Overview

We are seeking a Senior Embedded Software Engineer to own the deployment, security, and lifecycle management of mission-critical software running on extreme edge hardware. You will design hardened, containerized execution runtime environments, optimize computer vision deployments on heterogeneous accelerators, and ensure fault-tolerant, power-efficient execution in the harsh space radiation and thermal environment.

Key Responsibilities

1. Secure & Resilient Edge Containerization

• Architect, configure, and maintain secure, lightweight container execution environments (Docker, Podman, containerd) optimized for resource-constrained embedded systems and spaceflight hardware.
• Implement isolation, sandboxing, and resource fencing (cgroups, namespaces, seccomp, AppArmor) to run multi-tenant customer applications and onboard computer vision pipelines without risking flight avionics stability.
• Design robust, failsafe Over-the-Air (OTA) delta updates, atomic image rollbacks, and recovery mechanisms over low-bandwidth, intermittent satellite uplink/downlink passes.

2. Embedded Systems & Hardware Interfacing

• Develop, debug, and optimize systems software in C and Modern C++ across embedded Linux systems (Yocto, Buildroot, Ubuntu Core) and Real-Time Operating Systems (RTOS).
• Interface high-throughput satellite payloads (hyperspectral, multispectral, RGB optical, and SAR sensors) with onboard processing units using high-speed protocols (PCIe, MIPI CSI-2, GigE Vision, USB 3.0, CAN, SPI, UART).
• Implement hardware health monitors, thermal throttling controls, watchdog services, and autonomous recovery routines against Single Event Effects (SEEs/SEUs) caused by space radiation.

3. On-Orbit Computer Vision & AI Deployment

• Package, quantize, and deploy deep learning and computer vision models (object detection, small-target maritime tracking, cloud segmentation, feature extraction) directly onto embedded edge accelerators.
• Optimize inference performance and memory bandwidth on hardware platforms such as NVIDIA Jetson (Orin/Xavier), Edge TPUs, ARM Ethos/Mali, and FPGA-based neural accelerators utilizing TensorRT, ONNX Runtime, CUDA, or TVM.
• Benchmark and profile end-to-end vision pipelines (preprocessing pipelines, CV/DL models, compression etc.).

4. Verification, Testing & Mission Readiness

• Conduct Hardware-in-the-Loop (HIL) testing and flat-sat benchmarking using flight-representative System-on-Chips (SoCs) and payload emulators.
• Establish automated CI/CD validation pipelines to cross-compile, build, test, and sign containerized images for orbital target architectures.