Senior Robotics Engineer

InfoVision Inc.; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

InfoVision Inc. seeks a Senior/Lead Robotics and Edge Integration Engineer to lead the architecture, development, and deployment of intelligent edge systems and robotic platforms in Toronto, Canada.

You will bridge autonomous systems with 5G-enabled edge infrastructure, building resilient middleware and validating robotics workflows in high-fidelity simulations. You will guide senior/peer engineers, implement ROS 2, OPC UA, and VDA 5050, and optimize NVIDIA Jetson-based edge compute pipelines

Qualifications

• 6+ years of experience shipping production-grade embedded or robotic software.
• Strong ROS 2 architecture, lifecycle management, and DDS tuning expertise.
• Hands-on with OPC UA or VDA 5050 for AMR/AGV fleet coordination.

Responsibilities

• Middleware & Communication Engineering: Design, optimize, and maintain low-latency communication fabrics utilizing ROS 2, DDS (Data Distribution Service), and MAVLink for dependable multi-agent and embedded robotic systems.
• Industrial Protocol Integration: Implement and standardize machine-to-machine interfaces such as OPC UA and fleet management protocols like VDA 5050 to ensure seamless interoperability between autonomous mobile robots (AMRs) and automated factory systems.
• Embedded Edge Systems & Hardware Acceleration: Architect and optimize software stacks on embedded Linux environments and edge hardware platforms, specifically NVIDIA Jetson systems, leveraging hardware-accelerated processing for real-time applications.
• Simulation-Driven Development: Build, configure, and maintain advanced digital twins and robotic simulations using NVIDIA Isaac Sim and Isaac Lab to test autonomy algorithms, edge workloads, and fleet coordination protocols safely in virtual environments.
• Behavior Optimization & Controls: Design, implement, and debug complex robotic behaviors and state machines utilizing tools like Groot and BehaviorTree.CPP.
• Technical Leadership & Collaboration: Lead and mentor junior/mid-level robotics engineers, collaborate with cloud-native infrastructure teams to deploy edge gateways, and champion rigorous software engineering best practices within the robotics domain.

Skills

Leadership

Mentoring

Cross-team collaboration

Problem solving

Debugging

Technical communication

Education

BS/MS/PhD in Robotics or CS or EE

Tools

ROS 2

DDS tuning

OPC UA

VDA 5050

NVIDIA Jetson

JetPack

DeepStream

TensorRT

Groot

BehaviorTree.CPP

C++14/17/20

Python

Linux / Embedded Linux

NVIDIA Isaac Sim/Isaac Lab

Job description

Senior/Lead Robotics and Edge Integration Engineer

• Long term Contract

Job Purpose

As a Senior/Lead Robotics and Edge Integration Engineer , you will lead the architecture, development, and deployment of intelligent edge-computing systems and robotic platforms. You will bridge the gap between autonomous physical systems, industrial automation protocols, and 5G-enabled edge infrastructure. This role focuses on building resilient middleware ecosystems, optimizing embedded edge compute modules, and validating complex robotics workflows in high-fidelity simulations before deploying them to real-world industrial environments.

Key Responsibilities

• Middleware & Communication Engineering: Design, optimize, and maintain low-latency communication fabrics utilizing ROS 2, DDS (Data Distribution Service), and MAVLink for dependable multi-agent and embedded robotic systems.
• Industrial Protocol Integration: Implement and standardize machine-to-machine interfaces such as OPC UA and fleet management protocols like VDA 5050 to ensure seamless interoperability between autonomous mobile robots (AMRs) and automated factory systems.
• Embedded Edge Systems & Hardware Acceleration: Architect and optimize software stacks on embedded Linux environments and edge hardware platforms, specifically NVIDIA Jetson systems, leveraging hardware-accelerated processing for real-time applications.
• Simulation-Driven Development: Build, configure, and maintain advanced digital twins and robotic simulations using NVIDIA Isaac Sim and Isaac Lab to test autonomy algorithms, edge workloads, and fleet coordination protocols safely in virtual environments.
• Behavior Optimization & Controls: Design, implement, and debug complex robotic behaviors and state machines utilizing tools like Groot and BehaviorTree.CPP.
• Technical Leadership & Collaboration: Lead and mentor junior/mid-level robotics engineers, collaborate with cloud-native infrastructure teams to deploy edge gateways, and champion rigorous software engineering best practices within the robotics domain.

Required Qualifications

• Experience: 6+ years of experience in software development for autonomous systems, robotics, or edge computing, with a proven track record of shipping production-grade embedded or physical robotic software.
• Robotics Middleware: Deep expertise in ROS 2 (Robot Operating System) architecture, node lifecycle management, lifecycle nodes, custom messages, and DDS tuning (e.g., Fast DDS, Cyclone DDS).
• Industrial Automation & Fleets: Demonstrated hands-on experience integrating systems with industrial protocols like OPC UA or deploying VDA 5050 standards for AGV/AMR fleet coordination.
• Embedded Linux & Edge Compute: Extensive experience configuring and optimizing custom embedded Linux builds and implementing software pipelines on edge compute hardware, with deep technical knowledge of the NVIDIA Jetson platform ecosystem (JetPack, DeepStream, TensorRT).
• Simulation Platforms: Proficient in building physical simulations, sensor models, and synthetic data generation environments within NVIDIA Isaac Sim or Isaac Lab.
• Behavior Orchestration: Familiarity with designing and debugging hierarchical state machines and behavior trees, specifically using Groot.
• Core Software Skills: Strong proficiency in modern C++ (14/17/20) and Python, alongside structured debugging skills for real-time embedded environments.

Preferred Qualifications

• Experience designing and utilizing MAVLink-based communication systems for unmanned aerial vehicles (UAVs) or autonomous systems.
• Background in telecommunications or networking, particularly deploying robotics and edge workloads over private 5G or localized LTE networks.
• Academic degree (BS, MS, or PhD) in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or a closely related quantitative field.