Senior Software Developer - Real-Time Platform & Edge Systems

Description

PixelSight is a deep-tech startup that builds vision intelligence systems to tackle one of the hardest problems in perception: early detection of threats drones, boats, and other targets at the edge of what's visible. Our systems are deployed in the field and saving lives.

We're looking for a senior, hands-on software developer to own and evolve the real-time platform behind those systems the runtime that turns detection and tracking into one reliable system running on edge hardware, unattended, in the field.

Your ownership is the platform itself

process orchestration and inter-process messaging, latency and throughput budgets, camera and sensor I/O, deployment and updates on edge hardware, and the performance and reliability of the whole pipeline under real-world load. You'll integrate algorithmic modules into that runtime, and read and reason about their code well enough to debug the system end-to-end. The engineering satisfaction here is in taking something genuinely hard and making it run for months without anyone having to touch it.

Part of the role includes lower-level work on Linux-based systems close to the hardware, so systems experience is a strong plus. This is a good fit for someone who likes to take ownership, work across the stack, and help shape the product as it grows building meaningful, mission-driven technology that truly matters in the real world.

Requirements

• 6+ years of software engineering experience, including at least 3 years of building and shipping production software – Must
• Strong hands-on experience developing production systems in Python, C++, or Rust
• Proven ability to independently design, develop, and deliver end-to-end features within complex software systems
• Strong architectural judgment, including the ability to evaluate trade-offs in real-time, resource-constrained environments
• Ability to navigate, maintain, and improve large, evolving codebases with minimal guidance

Bonus skills

• Multi-process architecture and IPC — message passing, shared memory, queues, backpressure
• Real-time performance work — end-to-end latency profiling, frame budgets, jitter, throughput under load
• Edge deployment — NVIDIA Jetson, JetPack, ARM64, cross-compilation, over-the-air updates
• Linux systems — systemd, networking, containerisation, debugging on constrained devices
• C++ and/or Rust — a significant advantage for real-time work
• Camera and sensor integration — industrial SDKs, ONVIF, RTSP
• Edge inference deployment — TensorRT / ONNX Runtime engine build, caching and versioning (deploying models, not training them)
• GPU performance — CUDA streams and memory management, profiling
• Domain — safety-critical, defence, aerospace, robotics or autonomous-vehicle software