Top Tech Jobs & Startup Jobs in Toronto

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.

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.

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 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.

Design, build, and own end-to-end 3D asset pipelines and tooling for a multi-sensor simulation stack. Architect formats, storage, validation, packaging, and serving for meshes, neural representations, and generative outputs. Create visualization and curation tools at scale, integrate neural rendering and generative research into production, and collaborate with autonomy and safety teams to meet realism and coverage requirements.

The role involves building standardized training frameworks, profiling model performance, collaborating with teams, and improving related tooling.

The Applied Data Scientist will analyze performance data of Waabi's autonomy systems, develop automated dashboards, and collaborate across teams to drive insights for performance improvements.

As a Research Engineer in Sensor Simulation, you will develop multi-sensor rendering systems for self-driving technologies, collaborate with scientists and engineers, and work on innovative solutions using machine learning and neural rendering techniques.