Edge Performance Engineer - AI

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