We are looking for a motivated and talented IoT Systems Engineer to join our Toronto team and help us take our products to the next level in connectivity, reliability, and customer delivery.
Our Company
Invision AI is reshaping Intelligent Infrastructure and Transportation. Powered by a unique multi-camera stack that generates high-integrity 3D digital twins of dynamic environments, our technology powers disruptive, market-leading solutions in intelligent infrastructure with proven deployments across global markets. We provide real-world three-dimensional situational awareness - including 3-D detection, geo-localized tracking across sensors and sensor fusion. Our products include systems that accurately count passengers in free-flow vehicles under all weather conditions, automatic incident detection systems capable of identifying wrong-way drivers, stopped vehicles, and other traffic events in real time on roadways and railways.
The Role
This is a dynamic, hybrid role for a wearer of many hats. You will work across our products, moving comfortably between C++ development, Go, Elixir, Linux systems, networking, device connectivity, monitoring, hardware testing, and customer delivery.
We are looking for a tinkerer who enjoys seeing a product through, from code deployment to the customer's physical hands. This is not a narrowly focused software or IT role: you will implement and maintain features, help customers succeed, prepare hardware units for shipping, and periodically work in the field to test, deploy, and troubleshoot systems.
If you enjoy understanding how a complete product works and taking ownership across the full lifecycle of connected devices, keep reading.
Location
This is a full-time position based in Toronto downtown.
What You'll Do
- Develop, maintain, and troubleshoot C++ software running on Linux-based devices
- Implement new product features across device, connectivity, monitoring, and customer-facing workflows
- Implement and maintain signal processing algorithms (LIDAR, cameras)
- Diagnose and resolve networking, remote-access, and device-connectivity issues
- Maintain deployed systems and improve their reliability, observability, and performance
- Test hardware and software together to validate complete product behavior
- Prepare, configure, validate, and package hardware units before shipment to customers
- Support customers with technical questions, deployment needs, and issue resolution
- Participate in periodic field work for installation support, testing, deployment, and troubleshooting
- Build a deep understanding of our products and use that knowledge to improve the customer experience
- Write maintainable, well-tested code and clear technical documentation
- Participate in design reviews, code reviews, and technical planning
Requirements
Must Have
- 5+ years of relevant software, systems, IoT, embedded, or field engineering experience
- Experience with embedded or edge computing systems
- Strong C++ development skills
- Strong Linux systems knowledge, including deploying, configuring, and troubleshooting software on Linux-based devices
- Solid understanding of networking fundamentals, including IP networking, communication protocols, remote access, and troubleshooting connectivity issues
- The ability and interest to work across software, devices, hardware, connectivity, monitoring, and customer delivery
- Hands-on experience testing and troubleshooting hardware and software together
- A practical, detail-oriented approach to preparing and validating hardware units for shipment
- Strong problem-solving skills and the ability to understand complex products end to end
- Comfortable interacting directly with customers and translating technical issues into clear next steps
- Willingness to perform periodic field work for product deployments, testing, and troubleshooting
- Sound software engineering practices, including automated testing, code review, version control, and continuous integration
- Strong written and verbal communication skills
Bonus Skills
- Familiarity with device monitoring, observability, and remote fleet management
- Experience with Docker or other container technologies
- Experience with hardware integration, sensors, cameras, or industrial computers
- Familiarity with efficient serialization and communication protocols, such as protobuf, gRPC, MQTT, or NATS
- Experience with Elixir and Go
- Experience supporting technical products in customer or field environments
- Knowledge of computer vision, machine learning, or real-time video-processing systems
Benefits
- A Mission that Matters: The opportunity to work on projects that make the world safer and greener
- Excellence: A culture of very high technical standards where quality engineering is valued over quick hacks
- Technical Challenge: A wide variety of technology and tasks, including web development, distributed and edge computing, ML, real-time processing, and computer vision
- Growth Environment: Join an international team where your voice is heard and your impact is visible
- Compensation and benefits: Competitive salary package including equity, allowing you to share in the success you help build. Benefits: RRSP Plan, Health and Dental and 4 weeks holiday.
Massive amounts of data being created at the edge, uploading this data to the cloud for real-time analysis is neither financially nor technically feasible. Extracting meaning from this data is computationally intensive and expensive, limiting adoption of edge AI to a few high-value applications. After years of research by leaders in computer vision and machine learning we have developed technology that is two to three orders of magnitude more efficient than other high-accuracy deep learning systems. Our patent pending technology evolves the state of the art with a combination of optimization, sprinkled with unique insight and just a little magic. Video is our first application: the system is trained in the cloud by ingesting video where objects and activities of interest have been annotated. Learning is distilled into ultra-efficient software that runs on fixed, body-mounted and vehicle-mounted cameras. We can enable analytics on most professional IP video cameras with just a firmware update. Older cameras can be retrofitted with a low-power embedded processor, such as those from our partners NXP and Ambarella. Our software-only system gets smarter over time: edge cases (where the system is not very confident that it knows what is happening) are captured, uploaded to the cloud for analysis, and the learning distilled into ever smarter software. We work with more than just video: infrared, thermal, radar and lidar play important complimentary roles in helping to establish accurate, detailed situational awareness across a wide variety of environmental conditions. Each sensor detects, classifies and tracks multiple objects locally in real-time. This metadata is then push to the cloud, or a central ECU in the case of a vehicle, where it is fused to establish ground truth, detect behavior, track objects across multiple sensors, and identify anomalies.
Key team members
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