Start Date
Immediate
Expiry Date
02 Sep, 25
Salary
55000.0
Posted On
02 Jun, 25
Experience
5 year(s) or above
Remote Job
Yes
Telecommute
Yes
Sponsor Visa
No
Skills
Computational Physics, Storage Systems, Hardware Diagnostics, Reinforcement Learning, Computer Engineering, Robotics, Version Control, Physics Engines, French, Rust, Unreal Engine, Python, Pipelines, Multi Agent Systems, English, Simulations, Docker, C++, Containerization
Industry
Information Technology/IT
THE COMPANY
Humanitas is a young, award-winning innovator startup based in Montreal, specializing in emergency response and resilient technologies. Working with a list of world-class industry leaders and researchers, our team specializes in advanced telecom, simulation, visualization, cybersecurity, swarming robotics, edge computing, and more. Our multidisciplinary team also endeavors to universalize our technology and expand their applications to routine use cases beyond edge scenarios.
We are an ambitious group of young people who aim to contribute to a little change in the world by creating IT solutions that help people globally, especially when they need it most. Compassion is at the core of our business, and our collaboration is driven by our desire to challenge our limits and explore our potential.
EDUCATION:
EXPERIENCE:
TECHNICAL SKILLS:
THE ROLE: SENIOR SIMULATION SYSTEMS ARCHITECT
We are seeking a Simulation Systems Architect with deep expertise in designing and integrating advanced simulation ecosystems for training, testing, continuous learning, and deployment in complex, real-world environments.
This role is essential to the development of our comprehensive simulation pipeline — a platform enabling large-scale, synthetic data generation, real-time system testing, continuous model feedback, and automated deployment of decision-making systems. It supports applications spanning robotics, language interaction, perception, and federated or distributed systems. This role also includes responsibility for ensuring infrastructure scalability and performance, including simulation server configuration and hardware optimization.
KEY RESPONSIBILITIES
Simulation Architecture & Design
Lead the design of a modular, scalable simulation platform using engines like Unreal Engine, supporting multimodal synthetic data generation (vision, audio, text, tabular).
Define data standards, simulator APIs, and interfaces for deploying agents, collecting ground-truth metadata, and embedding domain randomization techniques.
Pipeline Implementation
Oversee end-to-end pipelines from synthetic data generation through data cleaning, normalization, storage, and integration with downstream processing (model training, LLM fine-tuning, etc.).
Configure local and cloud-based simulation servers to ensure sufficient memory, GPU availability, and I/O throughput for synthetic data rendering and real-time agent feedback.
Deployment & Infrastructure
Collaborate with DevOps and MLOps teams to deploy simulation environments across cloud, edge, and on-premise environments.
Select and tune hardware (CPU, GPU, memory, network) for specific simulation workloads (e.g., rendering, inference, or data streaming).
Benchmarking & Evaluation
Establish validation metrics and test harnesses for evaluating system performance under simulated and real-world scenarios.
Implement benchmarking standards for agents across RL, supervised learning, and fine-tuned LLMs within simulated tasks.
Cross-Team Integration
Work closely with ML researchers, robotics engineers, data scientists, and embedded developers to ensure simulations match deployment constraints and research needs.