Top Tech Jobs & Startup Jobs in Montreal

Build full-stack features and realtime web interfaces for the Autonomous Traffic Control platform. Develop frontend UIs (maps, telemetry) and backend services/APIs, integrate streaming feeds, and ship reliable, operational tools used by controllers, fleet operators, and drivers.

Develop and train conditioned policies and MARL systems to simulate realistic driving behaviors, implement safety-constrained RL algorithms, design rewards and evaluation metrics, optimize large-scale training pipelines, advance neural architectures for long-horizon planning and spatial reasoning, and integrate research models with production simulation and planning teams.

The Senior ML/RL Engineer will develop behavior models, implement RL algorithms focusing on safety, design reward functions and optimize training environments while collaborating across teams.

Responsible for designing and maintaining build and release pipelines for autonomous driving software, optimizing development workflows, and collaborating with teams.

The role involves designing and developing machine learning infrastructure for annotation, evaluation, and training models, focusing on scalable systems and efficient data workflows.

The role involves exploring ideas in deep learning, managing machine learning project life cycles, and collaborating on autonomous driving technology.

The Onboard Infrastructure Engineer will develop and maintain onboard infrastructure for autonomous vehicles, focusing on software reliability, system integration, and performance optimization.

Build high-performance, scalable simulation infrastructure and tooling for autonomous vehicle development. Design systems for scenario generation, simulation execution, synthetic data, and reinforcement-learning workflows. Collaborate with ML, perception, and controls teams to improve realism, performance, and validation pipelines while writing production-quality C++ and Python code, contributing to architecture, testing, and documentation.

Design, build, and ship backend services and frontend tools for fleet scheduling, dispatch, monitoring, maintenance, and operator workflows. Implement core features, build and consume APIs, work with databases and event-driven integrations, develop role-based operator tools, debug and improve production reliability, and collaborate with product and operations teams.

Design and build core operation platforms (scheduler, dispatcher, vehicle console, TMS) for autonomous trucking. Create durable object models, state machines, event-driven services, real-time operator tooling, APIs, and integrations. Ensure safety-critical workflows are observable and resilient while partnering with autonomy, operations, and product teams and driving engineering excellence.