Top Tech Jobs & Startup Jobs in Toronto

Designs and operates cloud infrastructure for large-scale ML training and production model serving. Responsibilities include distributed PyTorch training, GPU/TPU clusters, data pipelines for video and sensor data, infrastructure-as-code, CI/CD, observability, security, reliability, and developer tooling. The role partners across research and engineering, supports live customer-facing workloads, and mentors growing infrastructure teams.

Lead research and development of real-time, photorealistic 3D and 4D reconstruction models for spatial intelligence. Set the research agenda, guide architecture and training strategy, manage datasets and evaluations, and deploy models into production. Lead and grow researchers and infrastructure engineers while evaluating emerging research, contributing to publications and patents, and driving experimentation across multi-node GPU environments.

Supports founders and the Chief of Staff across operations, finance, administration, marketing, communications, office and people operations, sports events, logistics, vendor management, and special projects. The intern will manage projects end-to-end, build systems and processes, coordinate across functions, and help execute high-priority initiatives in a fast-paced, in-person startup environment.

ML Engineering Intern supporting real-time markerless motion capture systems. Responsibilities include deploying and monitoring pose estimation models in the cloud, curating training data, evaluating model performance, diagnosing failure modes, running experiments, and improving deployment and data tooling. The role requires 3D computer vision knowledge, Python proficiency, and familiarity with deep learning, with opportunities to work on cloud infrastructure, containerization, model optimization, and robotics middleware.

Lead the company’s technical execution engine by establishing planning systems, operating rhythms, and communication frameworks. Partner with founders and engineering leaders to drive high-impact initiatives across AI, computer vision, hardware, and cloud infrastructure. Own product launches, customer deployments, partner initiatives, risk management, cross-functional alignment, and scalable processes that improve engineering velocity and support company growth.

Build and optimize a cross-platform 3D viewing experience for web, mobile, and native platforms. Develop spatial and video data streaming pipelines, work with 3D geometry and rendering, and optimize performance across delivery and rasterization. Own UX and visual design, prototype solutions to compression and visualization challenges, collaborate with reconstruction teams, and contribute across rendering, frontend, mobile, and backend systems.

Leads the Capture Systems team and architects spatial data capture infrastructure using cameras, LiDAR, mechatronics, firmware, and software. Responsibilities include managing multidisciplinary engineers, setting technical direction, making hardware and software architecture decisions, driving calibration, sensor fusion, 3D reconstruction, and state estimation, partnering with leadership and downstream teams, and managing camera installation plans for large venues.

Design and develop embedded sensor drivers, firmware, and high-speed networking infrastructure for multi-sensor data capture. Optimize synchronization, latency, and video transfer while evaluating cameras, LiDAR, ultrasonic sensors, and other hardware. Design custom PCBs and collaborate with software, mechanical, and robotics teams on production-grade mechatronics systems.