Top Tech Jobs & Startup Jobs in Montreal

Design, test, and optimize electromechanical systems and motor control firmware. Specify and tune BLDC motors, harmonic drives, and gearboxes. Implement FOC firmware on microcontrollers and integrate industrial communications (EtherCAT, CAN). Collaborate with mechanical engineers on joint design and thermal management to improve efficiency and torque density.

Call for fresh graduates and students to submit a one-page resume and a cover letter (max 500 words) to register interest in entry-level and internship roles in Web3 and AI. Applicants should state country/visa status, desired sectors and roles, and can include portfolios or personal projects to demonstrate relevant skills.

Run adversarial tests on language and multimodal models, build guardrails and real-time filters for autonomous tool use, and support RLHF alignment and constitutional AI development to ensure safe AI deployment.

Design and implement functional safety systems for robotic products to meet ISO standards. Develop redundant safety-rated PLC architectures, implement collision-avoidance logic, and perform comprehensive FMEA on hardware and software.

Design and implement Visual-Inertial SLAM pipelines, dynamic obstacle avoidance, and predictive path planning. Optimize state-estimation and navigation algorithms for low-compute edge deployment on robotic platforms.

Lead product strategy and roadmap for AI and robotics products, translating VLA and agentic RAG breakthroughs into customer value, defining safety/usability/performance metrics, working with enterprise adopters, and driving cross-functional delivery.

Independent full-cycle recruiter managing sourcing, client engagement, offer negotiation, and placements using AI-driven tools. Acts as commercial advisor, provides market insights, and maintains self-directed billing and activity in a results-only, remote environment.

Develop and evaluate high-resolution tactile sensing and dexterous manipulation systems by processing tactile and force-torque data, implementing slip-detection and compliant control, training multi-fingered grasping policies, integrating solutions into robotic platforms, and conducting experiments to validate performance.

Optimize, compress, and distill large language and vision models for on-device inference. Build pipelines for distillation and hardware-specific compilation, and benchmark performance across NPU/GPU architectures.

Design, orchestrate, and optimize large-scale LLM pre-training across 1,000+ GPUs. Implement 3D parallelism, manage GPU clusters (SLURM/Kubernetes), optimize InfiniBand/RDMA networking and memory, and automate checkpointing and failure recovery for long training runs.