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Senior Robotics Engineer

InfoVision, Inc.Toronto, ON🇺🇸United StatesPosted Sep 24, 2026

Why This Role Stands Out

This hybrid role offers an exciting opportunity to lead the architecture and development of cutting-edge robotics and edge AI systems, bridging physical automation with advanced 5G infrastructure. You'll thrive here if you possess a passion for middleware engineering, embedded systems, and optimizing complex workflows in simulation and real-world deployments. Apply now to shape the future of intelligent automation!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Toronto, ON, United States
Posted
Yesterday
5GEdge ComputingRoboticsROS

Job Description

Senior/Lead Robotics and Edge Integration Engineer

  • Location: Toronto, Ontario , Canada - Remote
  • Long term Contract
  • Department: Robotics & Edge AI Engineering

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.

 

 

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