Edge Performance Engineer - AI

Full Description

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