Top Tech Jobs & Startup Jobs in Toronto

As a Research Engineer, you will integrate ML models into planning stacks, develop testing interfaces, and collaborate with teams to enhance autonomous truck capabilities.

Design and develop machine-learning approaches for vehicle control, including learned vehicle dynamics models, adaptive controllers, data pipelines, evaluation metrics, and simulation tooling. Integrate learned models into safety-critical closed-loop systems and validate algorithms through offline experimentation, simulation, and on-vehicle testing. Collaborate with engineers and research scientists to combine classical control with AI for scalable self-driving technologies.

Provide onsite and remote IT operations support, with a focus on Linux systems administration, networking, endpoint management, identity and access management, security compliance, and user support. Administer servers and workstations, troubleshoot networks, manage device lifecycles, document processes, support audits, improve workflows, and participate in an after-hours on-call rotation across Waabi’s locations.

Develop scalable, production-quality software for an autonomous vehicle platform. Responsibilities include building tools and frameworks for AV development, integrating web platforms with vehicles, creating customer-system integrations, deploying software, and collaborating with engineers, research scientists, commercial teams, and designers. The role offers hands-on experience in requirements identification, software development, and production deployment.

Develop and implement safety framework methodologies for autonomous trucking readiness decisions. Build high-signal safety datasets across simulation and closed-course testing, establish feedback loops from road monitoring and safety events, validate safety evaluation pipelines, and create traceable safety artifacts. The role also requires cross-functional collaboration, technical mentorship, data analysis, statistical evaluation, and evidence-based safety case development for autonomous vehicles.

Build and deploy internal AI tooling, agents, integrations, and workflows that improve productivity across engineering, research, and business teams. Evaluate emerging AI tools and models, develop observability and responsible-use guardrails, and partner with stakeholders to prototype and scale solutions. Drive adoption through documentation, enablement, and hands-on support while integrating AI into autonomy, simulation, ML training, and business workflows.

Own the design, deployment, security, and lifecycle management of Waabi’s multi-site network infrastructure. Responsibilities include switching, routing, wireless, firewalls, ISP planning, incident response, configuration hardening, IP addressing, segmentation, zero-trust access, vehicle connectivity, developer network support, on-premise compute networking, documentation, and disaster-recovery runbooks.

Develop signal processing algorithms for camera, LiDAR, radar, and other autonomous-driving sensor data. Design acquisition, fusion, filtering, and learning-based methods; optimize them for CPU, GPU, DSP, and specialized accelerators; and collaborate with autonomy and hardware teams to deliver reliable, low-latency production systems. The role also supports experimental validation and potential research publications.

Lead product design for Waabi’s driverless commercial and operations ecosystem, including fleet management, remote assistance, dispatch, monitoring, and safety-critical workflows. Observe fleet operators and terminal staff, design human-AI interactions, extend the design system, and ship directly in React codebases using AI-assisted tools. Collaborate with product, engineering, research, and operations teams while helping establish design culture and processes as the second product designer.

Lead software quality for autonomous vehicle planner architecture, developing fault-tolerant systems and improving reliability across motion planning and onboard software teams. Design motion planning software and decision-making algorithms for complex traffic scenarios, while managing experimentation and data-generation pipelines. Collaborate with multidisciplinary engineering and research teams to deliver safe, production-quality self-driving technology.