Edge Performance Engineer - AI
Location: Remote – Canada or Greater Toronto Area
A leading innovator in edge-based AI solutions is seeking a highly skilled Edge Performance Engineer to join their growing team. This cutting-edge role is at the intersection of hardware and AI, focusing on the optimization of GPU-accelerated vision pipelines running at the edge. This is a rare opportunity to influence the design and deployment of real-time computer vision systems across industrial and automation environments, with the support of a well-funded and visionary organization.
In this position, you'll take full ownership of the edge system performance lifecycle, from profiling and model optimization to system integration and observability. You’ll work cross-functionally with machine learning, DevOps, and cloud engineering teams to ensure consistent, high-throughput inference at the edge. The ideal candidate thrives in resource-constrained environments and enjoys solving complex system-level challenges involving hardware acceleration, system bottlenecks, and runtime tuning.
Key Responsibilities
- Optimize performance of GPU-accelerated computer vision pipelines on edge hardware (e.g., NVIDIA Jetson, x86/ARM systems).
- Improve throughput and reduce latency through advanced model optimization techniques (e.g., quantization, TensorRT, ONNX Runtime).
- Profile and resolve system-level constraints across CPU, GPU, memory, storage, and network layers.
- Collaborate with machine learning teams to deploy robust models that meet real-world resource constraints.
- Integrate edge systems with observability and orchestration frameworks to ensure maintainability and scale.
- Develop dashboards and tools to monitor edge performance KPIs like frame rate, latency, uptime, and resource usage.
- Participate in root cause investigations for performance-related incidents on production systems.
- Provide technical input on system design and hardware selection for new edge deployments.
What You'll Bring
- 5+ years of experience in software engineering with a focus on high-performance or real-time systems.
- Strong background in GPU-accelerated development using CUDA, TensorRT, cuDNN, or equivalent vendor tools.
- Proficiency in Python and at least one systems language such as C++ or Rust.
- Proven experience in deploying and optimizing deep learning inference pipelines in production environments.
- Advanced Linux skills and comfort using observability tools (e.g., perf, strace, eBPF).
- Experience working with Docker and CI/CD workflows targeting edge devices.
- Deep debugging capabilities across application, system, and hardware levels.
Preferred Qualifications
- Background in edge AI, robotics, or industrial automation applications.
- Familiarity with video processing frameworks (e.g., GStreamer).
- Understanding of edge-specific challenges such as thermal throttling, intermittent connectivity, and limited bandwidth.
- Exposure to Kubernetes or other edge orchestration frameworks.
Why Join
- Work at the forefront of AI and computer vision innovation.
- Solve tangible, high-impact problems in real-world deployments.
- Join a mission-driven team with strong technical leadership and cross-functional collaboration.
- Enjoy a flexible, remote-first work culture with top-tier talent across Canada and beyond.
About Blue Signal:
Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
